389 jobs found

# QA LeadApply nowGlobal TechnologyFull timeUnited Kingdom - LondonJR214Posted 3 weeks agoQA LeadAs QA Lead you wil be responsible for shaping and driving the quality assurance strategy across the developing technology ecosystem, balancing the need for rapid progress and sustainable quality as the business and systems evolve. Working closely with Architecture & Engineering, Product and Business teams, you will establish best practices, build confidence in our quality and release processes and foster a 'right first time' culture where quality is a shared responsibility.This is a hands-on leadership role in a rapidly growing organisation. You'll define QA standards, establish testing practices through third party arrangements and embed automation from day one; you will also be a contributor to business interactions, partner leadership and strategy & report development.The environment is a combination buy, build and AI / agentic tools distributed across the workforce. Key Responsibilities + Define and own the QA Strategy, processes and standards across the software development lifecycle. + Develop and maintain a scalable testing framework that supports manual testing but which emphasises automated testing. + Lead test planning, execution, defect management and release readiness activities across multiple product teams. + Work closely with Product Managers, Engineers, Business Analysts, and stakeholders to define acceptance criteria and ensure quality is embedded from the earliest stages of development. + Drive test automation actively across all products and projects. + Establish quality metrics, reporting and dashboards to product transparency regarding quality and progress. + Continuously improve QA processes, tools and methodologies to support rapid and reliable software delivery. Deploy methods and tools suited to an agentic development environment across applications and data lakehouse. + Ensure testing activities support security, performance, resilience and compliance relevant to a regulated business. Ensure testing of data lakehouse, supports classification, rights access & rights to use, traceability, integrity security and availability. + Contribute to the continuous evolution of our engineering culture by promoting collaboration, ownership and continuous improvement.About YouYou are an experienced QA professional who combines strong technical expertise with a pragmatic, collaborative approach to driving up quality whilst ensuring progressive delivery. Comfortable operating in a small, dynamic, multi-region, multi-partner matrix organisation. You are self-starting, open, striving for better, adaptable and motivated by continuous improvement. Skills and Experience + Proven experience leading Quality Assurance within an agile software development environment. + Strong understanding of QA methodologies, testing strategies and SDLCs. + Designing and implementing automated testing frameworks and tools. + Hands-on experience with API integration, functional, regression, end-to-end testing, and adept at supporting through User Acceptance + Knowledge of CI/CD pipelines and integrating automated testing into deployment workflows. + Experience of testing modern data platforms built on a Lakehouse architecture, ensuring the quality, integrity and reliability of data across ingestion, transformation storage and consumption layers. + Familiarity with cloud-based platforms such as Databricks or Snowflake. + Familiarity with observability tools and techniques to proactively identify data quality issues and pipeline failures. + Experience using test management and defect tracking tools such as Jira, Azure DevOps and similar + String understanding of risk-based testing and quality governance. + Ability to analyse complex systems and identify areas of potential quality risk. + Excellent written and oral communication skills, with the ability to explain business issues to technical teams and technical issues to both technical and non-technical audiences. + Previous experience working within insurance, reinsurance industries is highly desirable as is experience of high growth scale-up environments. About Willis ReWe combine specialist broking with analytics, modeling and research to help insurers optimize risk transfer, strengthen balance sheets and achieve sustainable growth. Our approach is relationship-driven, transparent and outcome-focused.At the heart of Willis Re is a focus on delivering the most cutting-edge analytical solutions to enable more informed, better decision-making for risk selection, portfolio optimization, and capital management.The launch of Willis Re brings a strategic advantage of being unhindered by legacy, an ability to leverage data, statistical models and advanced technologies with the best knowledge and expertise to deliver more efficient and effective reinsurance outcomes. This places Willis Re in a unique position to build a truly analytically driven business, focused on creating solutions for the reinsurance industry that are future led and forward thinking.Willis Re will also leverage recognized technical expertise from WTW's Insurance Consulting & Technology business including their advanced modeling and analytical capabilities. Alongside this will be WTW's Research Network, an award-winning business supporting and influencing science to improve the understanding and quantification of risk.

Indicium AI was Anthropic's first European launch partner - and sits among a handful of organisations globally trusted by Anthropic to deploy Claude at enterprise scale. We are also one of the first four OpenAI partners in the UK, and Databricks Ventures has invested in our business and holds a seat on our board. Our engineers have access to the latest AI tools and models, partner technical teams, and early capability previews that the wider market does not. We are deploying production AI systems into the world's most complex organisations across Financial Services, Energy, and Healthcare. We exist to make AI a genuine competitive advantage for our clients, not in a presentation but in production. We invest seriously in our people. Every FDE at Indicium AI has access to Anthropic training, and a flexible learning budget to go with it. All of our staff are equipped with Claude licenses for Chat, CoWork and Claude Code. We are building a team of engineers who are at the frontier - and we support that with the investment to match. The Role AI is not just changing what software can do - it is changing how software gets built. The best engineering organisations in the world are rewriting their operating models around AI native development: Claude Code in every workflow, agents across the SDLC, and a fundamentally different relationship between engineers and the tools they use. Most enterprises know this matters. Very few know how to make it work. The Forward Deployed Software Engineer at Indicium AI embeds directly with client engineering teams to transform how they build software. You do not wait for a brief. You watch how a team actually works, find the problems they have not articulated yet, and ship the changes that make AI native engineering real - not as a presentation, but in their daily workflows and production pipelines. This is a role for an experienced software engineer who is passionate about how AI is transforming the craft of software engineering. You will help organisations redesign their engineering capability - from how they use Claude Code and agentic tooling, to how they structure teams, review code, test, and ship. Then you will co-engineer alongside their teams to integrate these new ways of working into their product engineering workflows. You will lead engagements at some of the most complex organisations in the UK. Technically, commercially, and in the room with engineering leaders who have built serious systems and are not easily impressed. What You Will Do Lead engagements that transform how enterprise engineering organisations build software - from discovery and assessment through to embedded co engineering and operational handover Design and implement AI native development workflows: Claude Code integration, agentic coding assistants, AI augmented testing, automated code review, and intelligent CI/CD pipelines Define and roll out operating models for AI native engineering across client organisations - covering tooling, process, team structure, and best practice at scale Co engineer with client product engineering teams, working shoulder to shoulder to integrate new ways of working into their existing codebases and delivery cadence Own the client technical relationship at senior engineering leadership level - you are the person the VP Engineering or CTO calls, not one of the people copied on the email Navigate organisational complexity - procurement, security, resistant teams, shifting priorities - without losing delivery momentum Identify and shape new opportunities within existing client relationships - commercial awareness is part of the role, not separate from it Codify repeatable patterns and playbooks for AI native engineering transformation that let the practice scale beyond individual engagements Mentor engineers on your engagements and raise the bar for the practice through knowledge sharing Work alongside Anthropic field teams on joint client engagements - representing Indicium AI at the highest level What We Are Looking For 5+ years as a software engineer with strong production experience - you have built and shipped real systems, not just advised on them Deep passion for how AI is transforming software engineering - you are already using Claude Code, Copilot, or agentic development tools daily and have a clear view on where this is heading Experience in a client facing technical role - forward deployed engineering, technical consulting, solutions architecture, or engineering leadership with external stakeholders Strong proficiency in modern software engineering stacks - Python, TypeScript, or Java - with comfort across cloud platforms (AWS, Azure, GCP) Experience driving engineering process change or transformation within organisations - you have helped teams adopt new tools, practices, or ways of working at scale Genuine enterprise experience - you have navigated the realities of large engineering organisations: legacy systems, compliance requirements, multi team coordination, and stakeholder management High agency - you do not wait to be told what to do in an ambiguous situation, you make a call, communicate it, and deliver Vertical depth in at least one of Financial Services, Energy, or Healthcare - enough to be a credible peer, not just a technology generalist Nice to Have Experience with MCP server development, Claude Code enterprise deployment, or AI agent integration into development workflows Track record of defining engineering best practice or developer experience within a scaling organisation External presence - writing, speaking, or community contribution in the software engineering or AI tooling space Experience working alongside or within partner ecosystems such as Anthropic, Databricks, or AWS Why Indicium AI Access to leading AI Labs Anthropic's first European launch partner. One of the first four OpenAI UK partners. Databricks Ventures invested and on our board. Our engineers work with capabilities before the wider market does and work jointly with teams from leading AI Labs on customer delivery. We are builders We embed, we architect, we build - and we stay until it works. Our engineers make real decisions on live systems, for clients in industries where getting it wrong has consequences. There are no layers between you and the work. Problems worth solving No two engagements are the same. The variety and complexity of enterprise AI problems at Indicium AI is something a product company simply cannot offer. If you want engagements that test every dimension of what you can do, this is where they are. Investment in staying at the frontier The best engineers we know are relentlessly curious - and we build an environment that supports learning and growth. Every engineer has access to leading AI training and tools, career development pathways, and a flexible L&D budget. We think that's how it should be.

About WeBuild-AI: WeBuild-AI are AI natives delivering 10x value for enterprise organisations. We combine highly skilled experts with our AI Launchpad, industry-aligned language models, and agents to transform enterprise organisations into AI-powered and data-driven businesses. We work with enterprise organisations on a global stage, reinventing how they design, build, and operate AI powered software at scale with speed. Our Purpose: We're on a mission to reinvent what's possible with AI in enterprise environments. Our AI Engineers don't just implement solutions-they discover new patterns of working with AI that revolutionise entire business processes. We believe AI will fundamentally transform how organisations operate, and we're looking for pioneers who want to lead this transformation, working at the absolute cutting edge of what's possible with today's most advanced AI technologies. Role Overview: As a Principal AI Engineer at WeBuild-AI, you will design, develop, and deploy innovative AI solutions that transform our clients' businesses. You'll leverage cutting-edge language models, agent frameworks, and our Pathway platform to create high-impact AI applications that deliver 10x value. You'll be given the freedom to experiment and push boundaries, discovering new ways AI can solve complex enterprise challenges. Key Responsibilities Define the overall AI architecture and technology strategy, ensuring long-term scalability and reliability. Lead technical direction across multiple teams, overseeing the full AI solution lifecycle - from concept to production. Mentor and guide Lead AI Engineers and technical contributors to raise the engineering bar. Champion best practices for governance, observability, and lifecycle management of AI systems. Evaluate and introduce emerging frameworks, including Autogen, LangGraph, and other agentic ecosystems. Partner with senior stakeholders to align AI strategy with business goals. Drive the evolution of our internal platform (Pathway) to enable faster, safer AI delivery. Represent the company externally as a technical authority - at client workshops, conferences, or thought leadership sessions. Proactively identify and mitigate risks in AI adoption, ensuring ethical and compliant implementation. Required Skills & Experience Deep experience architecting and scaling enterprise-grade AI/ML systems. Proven expertise with cloud AI ecosystems (AWS Bedrock, SageMaker, Azure OpenAI, Azure ML). Strong command of agent frameworks, vector databases, and LLM orchestration tools. Ability to lead multi-disciplinary teams and manage complex AI projects. Advanced proficiency in Python, MLOps, and software engineering principles. Experience setting technical standards, governance frameworks, and performance benchmarks. Strong consulting mindset with the ability to translate emerging technology into business impact. Strategic thinker with the ability to pioneer new approaches and challenge conventional wisdom. The Mindset We Value: Relentless Innovation: We're looking for individuals who are constantly exploring the edges of what's possible with AI. You should be the type who stays up late testing new approaches just to see what might work. Flexible Methodology: Traditional development approaches don't always apply to AI. We need people who can adapt their working methods to the unique characteristics of AI systems, embracing experimental approaches when appropriate. "Can Do" Attitude: When faced with a seemingly impossible challenge, your response should be "let's figure out how" rather than "it can't be done." We value determined problem-solvers who find a way forward. Balanced Perspective: While pushing boundaries, you must maintain a grounded understanding of enterprise realities, balancing innovation with practical implementation. Growth Opportunities: Develop expertise with emerging AI models and capabilities before they reach mainstream adoption. Create intellectual property and novel implementation approaches. Work across multiple industries to develop deep domain expertise. Contribute to the evolution of our proprietary AI methodology. Participate in the AI research community and establish thought leadership. Shape new AI services and capabilities within our Pathway platform. This role is hybrid and we come into our London based office 3 days a week.

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We're training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us! Why This Role? We're seeking an experienced Program Manager to join Cohere's customer-facing Program Management team, with a focus on UK public sector and defence accounts. This is a highly specialised role requiring an individual who understands technical program delivery, the technical complexity of frontier AI models and the unique requirements of government and defence organisations. You will be the critical bridge between our cutting-edge AI capabilities and the specific needs of UK Government and defence organisations. You'll navigate complex procurement processes, stringent security requirements, data sovereignty concerns, and regulatory compliance while ensuring our customers successfully deploy and scale our AI solutions. In this role, you'll collaborate with our Strategic Customer team, Applied ML (AML) Engineering, Forward Deployed Engineering (FDE), Platform, Product, and Go-to-Market teams, serving as the technical program lead and trusted advisor for our most sensitive and high-impact government engagements. Location: UK Security Clearance: Active Top Secret clearance preferred; candidates with Active Secret clearance or those who are eligible and willing to obtain clearance will also be considered. What You'll Do Customer Program Leadership: Own end-to-end technical program delivery for UK public sector and defence customers, from initial deployment through production scaling Serve as the primary technical program point of contact for government customers, building trusted relationships with departmental CIOs, IT directors, and technical teams Translate complex government requirements (security, compliance, accessibility, bilingualism, data sovereignty) into actionable engineering plans Navigate government procurement processes, RFP responses, and contractual technical obligations. Strategic Communication: Provide clear, timely, and objective communication across Cohere's engineering organisation, customer stakeholders, and government leadership Translate between AI/ML technical concepts and government-appropriate language for decision-makers who may not have deep technical backgrounds Present technical roadmaps and status updates to senior government officials and departmental executives Represent Cohere's technical capabilities in sensitive government and defence contexts. Complex Program Management: Create and manage project schedules that account for government timelines, security review processes, and ministerial approval cycles Identify and manage dependencies across government departments, security authorities, cloud service providers, and internal Cohere teams Navigate risks unique to government deployments: privacy compliance, security authorisations, technical and infrastructure constraints Drive alignment between product development priorities and specific government requirements. Technical Delivery & Execution: Ensure on-time delivery of AI solutions that meet government-grade security, privacy, accessibility, and performance standards Coordinate technical work across multiple teams: model customisation, security hardening, integration with government systems, bilingual support Establish governance checkpoints appropriate for high-stakes government deployments Problem-solve complex technical challenges in air-gapped, on-premises, or highly regulated environments. You May Be a Good Fit If: Required Experience: 6+ years of experience as a customer-facing Technical or Engineering Program Manager in AI/ML consulting, technology transformation, or enterprise software delivery. Excellent executive communication and stakeholder management. Experience working with government, defence, or heavily regulated customers (public sector, defence contractors). Proven track record managing complex, multi-stakeholder technical programs with stringent compliance requirements. Bachelor's degree in a relevant field; advanced degree or technical certs a plus. Technical Background: Strong understanding of enterprise software deployment architectures (cloud, on-premises, hybrid, air-gapped) Working knowledge of or experience with modern AI: LLMs, agentic systems, MCP, RAG, fine-tuning, evals, and responsible AI would be a strong differentiator Comfortable discussing API integrations, model inference, data pipelines, and ML operations with technical stakeholders. Government & Defence Acumen: Deep understanding of how government organisations procure, evaluate, and deploy technology Familiarity with UK government requirements: data sovereignty, privacy laws (Privacy Act), accessibility standards, official languages obligations, security classifications Understanding of defence and national security considerations in AI deployment Experience with Algorithmic Impact Assessments or AI ethics frameworks is a strong asset Eligible to obtain UK government security clearance (Top Secret preferred) Nice to Have: Active UK government security clearance (Secret or Top Secret) - preference for active Top Secret clearance Background in or strong familiarity with UK defence, intelligence, or critical infrastructure sectors Experience with GC Cloud services (Azure, AWS GovCloud) or Protected B/C environments Project management certification (PMP, PgMP) or government-specific methodologies. Security Clearance Requirements This role requires eligibility for UK government security clearance. Preference will be given to candidates who currently hold an active UK government Top Secret (TS) clearance, as this will enable immediate engagement with our most sensitive defence and national security customers. However, we will also consider exceptional candidates who: Currently hold UK government Secret clearance and are eligible for TS upgrade Do not currently hold clearance, but are eligible and willing to undergo the Top Secret clearance process Have a previous government security clearance that has lapsed Please note that obtaining Top Secret clearance can take 12-18 months. Candidates without active clearance will work on non-classified public sector accounts while the clearance process is underway. What Makes This Role Unique This isn't typical program management- it's a highly specialised role at the intersection of frontier AI, national security, and public sector digital transformation. You'll work on some of the UK's most sensitive and impactful AI deployments, helping government organisations harness cutting-edge technology while maintaining the highest standards of security, ethics, and accountability. If you're passionate about responsible AI adoption, understand the unique constraints and opportunities within government, and want to have an outsized impact on how the UK leverages AI to serve its citizens, this role is for you. Full-Time Employees at Cohere enjoy these Perks: A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. Full health and dental benefits, including a separate budget for mental health. RRSP matching, 401K, Pension Scheme. 100% Parental Leave top-up for up to 6 months, for either parent. Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. 6 weeks of paid vacation (30 working days!) Budget for traveling to other offices if you are remote, plus an annual company offsite. How and Where We Work: Cohere is remote-friendly. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming soon. For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. For those not near an office: a co-working benefit so you can work alongside others in your city. Everyone receives a $500 home office stipend to set up your workspace properly. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.

Job Description We Are Accenture Song Accelerates growth and value for our clients through sustained customer relevance. Our capabilities span ideation to execution: growth, product and experience design; technology and experience platforms; creative, media and marketing strategy; and campaign, content and channel orchestration. With strong client relationships and deep industry expertise, we help our clients operate at the speed of life through the unlimited potential of imagination, technology and intelligence. Visit us at: The Data & AI Team The Data and AI revolution is changing everything. It's everywhere - transforming how we work and play. Join Accenture and help transform leading organisations and communities around the world. Accenture Data and AI is driving these exciting changes and bringing them to life across 40 industries in more than 120 countries. Accenture's Data and AI practice covers the range of Data and AI skills, from Strategy, Data Science, Data Architecture, AI Engineering and Visual Insights. When combined with Accenture's broader Strategy and Consulting practice, we are able to bring together the unique ability to drive end to end business change through the application of Data and AI. In the Data & AI Team You Will Be at the forefront of the industry, creating and owning AI solutions that make a real impact for clients Become an integral part of our Data & AI Song team with the credibility, expertise and insight clients depend on Work with famous brands and household names Drive and implement real world AI solutions into production that deliver measurable business value Work alongside global teams to collaborate and deliver the best solutions for our clients Build reusable AI assets and best practices that influence how consulting is delivered at scale As a Customer AI Developer Specialist, You Will Play a key part in delivering impactful Machine Learning (ML) and Generative AI solutions across a variety of industries. You will build and ship AI-powered products - from problem definition through to deployment and iteration - operating at the intersection of data science, technology, and business strategy. We Need Builders & Solution oriented people This role is for someone who sees a problem and instinctively starts building. Not waiting for perfect requirements. Building. We look for people who see the gap and can't help themselves - they're already sketching the solution. You thrive when a problem is messy and ill-defined. You know how to cut through complexity, run a quick experiment to test your assumptions, learn what is working, and iterate fast. You measure your success by what ships and the impact it creates - not by the elegance of your design document. You are energised by ambiguity, not paralysed by it. When a solution doesn't work, you debug it, rethink your approach, and try again. You leave things better than you found them - cleaner, faster, more scalable - because continuous improvement is how you naturally operate. Key Responsibilities Machine Learning & AI Development Solve complex, real-world business challenges using advanced ML and Generative AI techniques Design, build, and ship AI-powered tools, services, and experiments end-to-end Implement and optimise agentic AI workflows, multi-step reasoning pipelines, and RAG architectures Define strategies to embed, scale, and optimise ML models in production environments Experiment rapidly with new approaches - test early, learn fast, improve continuously Stay current with emerging AI research, tools, and techniques - and apply them before they become mainstream Product Mindset & Delivery Break complex problems into simpler, testable, scalable components Take full ownership - from idea to deployed solution - without waiting to be told what to do next Balance speed of experimentation with robustness, security, and maintainability Document patterns and best practices to enable reuse and scaling across the practice Operate confidently in ambiguity - define the path forward when requirements are unclear Business Impact & Collaboration Translate business problems into AI solutions with clear, measurable value Communicate technical concepts clearly to senior client leadership and non-technical stakeholders Contribute to capability building and knowledge sharing across the Data & AI practice What You Will Bring Required - Technical Skills Advanced Python - writing clean, production-grade code, not just scripts (OOP, async, packaging, testing) Generative AI & LLM development - prompt engineering, fine-tuning, RAG pipelines, context window management Agentic AI frameworks - LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflows Machine Learning - model development, training, evaluation, and deployment APIs & backend development - FastAPI, REST APIs, microservices architecture Vector databases & embeddings Cloud platforms - Azure GCP, or AWS; deploying and managing AI/ML workloads at scale Version control & MLOps - Git, CI/CD pipelines, model versioning, monitoring in production Data handling Required - Experience & Mindset Demonstrated end-to-end delivery: problem > build > deployed solution > iteration Strong experience with Generative AI in production - not just experimentation A track record of building working solutions, not just prototypes or proofs of concept Hands on experience with LLM tooling (Claude, GPT-4, Gemini, or equivalent) Strong analytical and problem solving skills - you debug fast and think in systems Comfortable working with messy, incomplete requirements and driving clarity through action English fluency and comfort working in global, cross functional teams Preferred Experience with NLP, computer vision, or multimodal AI models Knowledge of AI safety, guardrails, and responsible AI practices in production Familiarity with Snowflake, Databricks, or similar data platforms Prior experience acting as an AI champion or innovator within a larger organisation Consulting or client facing delivery experience Bachelor or Master degree in Computer Science, Data Science, Engineering, or related field Key Competencies Solution oriented mentality - sees a problem, starts building, ships, improves Experimental mindset - runs fast tests, learns from failure, iterates without ego Strong execution and delivery orientation Advanced AI engineering and Generative AI expertise Collaborative team player Curiosity and commitment to continuous learning What's in it for You Total Rewards 25 days of leave per year plus 3 extra volunteering days for charitable work of your choice Family-friendly and flexible work policies Attractive pension plan with financial wellbeing support and resources Private healthcare insurance plan and Mental Wellbeing support Employee Assistance Programme, Career Development and Counselling A range of generous Parental Leave offerings Locations London Additional Information Equal Employment Opportunity Statement All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. Accenture is committed to providing veteran employment opportunities to our service men and women. Please read Accenture's Recruiting and Hiring Statement for more information on how we process your data during the Recruiting and Hiring process. About Accenture We work with one shared purpose: to deliver on the promise of technology and human ingenuity. Every day, more than 775,000 of us help our stakeholders continuously reinvent. Together, we drive positive change and deliver value to our clients, partners, shareholders, communities, and each other. We believe that delivering value requires innovation, and innovation thrives in an inclusive and diverse environment. We actively foster a workplace free from bias, where everyone feels a sense of belonging and is respected and empowered to do their best work. At Accenture, we see well-being holistically, supporting our people's physical, mental, and financial health. We also provide opportunities to keep skills relevant through certifications, learning, and diverse work experiences. We're proud to be consistently recognized as one of the World's Best Workplaces . Join Accenture to work at the heart of change. Visit us at . Required - Technical Skills Advanced Python - writing clean, production-grade code, not just scripts (OOP, async, packaging, testing) Generative AI & LLM development - prompt engineering, fine-tuning, RAG pipelines, context window management Agentic AI frameworks - LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflows Machine Learning - model development, training, evaluation, and deployment . click apply for full job details

London, United Kingdom Job Description Function: Data & AI Solutions Location: Hybrid, London office Curious about what's next? So are we. Join Compare the Market and help to make financial decision making a breeze for millions. At Compare the Market, we're a purpose-driven business powered by tech and AI. We're building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers. We've carved a meerkat-shaped niche and we're looking for ambitious, curious thinkers who thrive in a fast-moving, high-impact environment. If you love accountability, embrace challenge, and want to make a real difference, you'll fit right in. We'd love you to be part of our journey. Compare the Market is building AI systems that connect directly to how millions of people in the UK find and buy financial products - and as a Senior Machine Learning Engineer, you will play a central role in making those systems production-ready. That means owning the engineering that takes ML models and AI capabilities from experimentation into reliable, scalable production use: the pipelines, the deployment tooling, the monitoring, and the shared components that make the whole thing work. This is a hands-on role with real technical scope. You will work closely with data scientists, engineers, and product teams - contributing to architecture decisions, raising engineering standards, and building the reusable tooling that raises the pace and quality of delivery across a fast-moving and expanding set of AI capabilities and systems. Some of the great things you'll be doing: ML Engineering and AI Systems Own the end-to-end delivery of production machine learning and AI solutions in collaboration with data scientists and product teams Design and build model pipelines for training, validation, and deployment using modern tooling (e.g.MLflow, Kubernetes) Contribute hands on code to model packaging, deployment, and lifecycle automation Build systems thatmonitormodel performance, drift,reliabilityand operational health in real time Support both batch and real time ML workloads depending on use case requirements Work on emerging AI and LLM powered capabilities, helping integrate modern AI techniques into production systems where they can deliver real user value Platform and Standards Help evolve our internal ML and AI platform to support experimentation, governance, and collaboration Define and promote best practices for ML and AI system design, including reproducibility, testing, CI/CD, model and agent observability and evaluation Develop shared tools and libraries that accelerate safe, efficient, and scalable ML development Collaboration and Technical Leadership Work closely with data scientists toproductioniseexperimental models and turn prototypes into robust services Act as a technical mentor and code reviewer for other engineers and contributors Provide technical leadership across ML and AI initiatives, contributing to architecture discussions and design reviews Culture and Innovation Contribute to a culture of engineering excellence, collaboration, and continuous learning Stay up to date on emerging tools and approaches inMLOpsand applied AI, helping evaluate and adopt technologies where appropriate Support responsible AI practices, contributing to explainability, auditability, and fairness in ML systems What we'd like to see from you: The Essentials Hands on experience with LLM-based systems: prompt engineering, RAG, tool use, or orchestration frameworks such asLangGraphorLangChain Familiarity with multi-step AI patterns - building systems where models plan, retrieve information and take sequences of actions Strong experience deploying ML models into production in cloud-native environments Solid software engineering skills in Python, with experience building scalable services, APIs, and production-quality code Experience with modern ML tooling and platforms (e.g.Databricks,MLflow, Airflow, Kubeflow, SageMaker, Vertex AI) Familiarity with CI/CD pipelines and infrastructure-as-code (e.g.Terraform, CloudFormation) Experience building robust, maintainable, and testable ML pipelines and APIs, including batch or real-time model delivery Strong understanding of ML lifecycle challenges - versioning, testing, monitoring, governance Excellent collaboration and communication skills, with experience working across data science, engineering, and product teams Nice to Have Active personal use of AI assisted or agentic coding tools, and an interest in how similar patterns could be applied to automate and accelerate ML engineering workflows - candidates who are exploring this space, even at an early stage, are encouraged to talk about it Experience in financial services,insuranceor another regulated sector Experience deploying real time or streaming ML models (e.g.Kafka, Flink, Spark Structured Streaming) Passion for automation, tooling, and building reusable systems Interest in responsible AI and ML model governance Why Compare the Market? We're a business built for pace and performance. Here, you'll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress. We believe diverse teams make better decisions, and we're committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive. If you're ready to stretch yourself, raise the bar, and grow with a team that's serious about performance, innovation, and purpose, we'd love to hear from you.

Senior Data Scientist, Artificial IntelligenceApplyremote type: Hybridlocations: London, United Kingdomtime type: Full timeposted on: Posted Todayjob requisition id: JR260XP-TEE Who We Are FTI Consulting is the leading global expert firm for organizations facing crisis and transformation. We work with many of the world's top multinational corporations, law firms, banks and private equity firms on their most important issues to deliver impact that makes a difference. From resolving disputes, navigating crises, managing risk and optimizing performance, our teams respond rapidly to dynamic and complex situations.At FTI Consulting, you'll work side-by side with leaders who have shaped history, helping solve the biggest challenges making headlines today. From day one, you'll be an integral part of a focused team where you can make a real impact. You'll be surrounded by an open, collaborative culture that embraces diversity, recognition, professional development and, most importantly, you.Are you ready to make your impact? About The Role Data scientists on FTI's AI Build Team should have a pragmatic approach to problem-solving and be capable of developing end-to-end solutions that clients can rely on in production. They should be capable of challenging their own work and finding a balance between perfection and practicality.FTI's AI build team is technology-agnostic with software engineering expertise to deploy advanced ML/AI methodologies at scale. Our engagements include using NLP for automated document classification, geospatial modeling of electric vehicle demand, demand forecasting, predictive maintenance, price optimization, and developing and maintaining production-grade agentic RAG systems that serve the entire firm.As a Data Scientist, you will research solutions and deliver high-quality outcomes with minimal guidance from Senior Data Scientists. You will mentor junior colleagues and lead sub-projects on larger initiatives. What You'll Do Data Management Perform data availability/quality assessments Develop comprehensive ETL processes Data Analysis Perform exploratory data analysis and render key insights through evidenced results Execute data quality assessments Illustrate material understandings through coherent data visualizations Execute and tune statistical analyses Modeling Conduct necessary research for proof-of-concept model selection Identify viable model features and apply appropriate normalizations Appropriately log model parameters and metrics for comparison Diligently optimize current processes and pipelines Perform quality control Actively work on ModelOps design and implementation Engineering Develop data pipelines and models that are well designed and auditable Develop production ready code that is scalable, maintainable, and adheres to best design principles Develop scalable Gen AI solutions Communication Frequently partner with internal and external stakeholders both technical and non-technical Provide guidance to junior data scientistsThis is an excellent opportunity for a person with proven data science experience to join a growing, dynamic team, and work on a variety of projects in a wide range of industries. Data Scientists will have opportunities to collaborate laterally and vertically, internally, and externally, as well as contribute to projects through developing various approaches to complex issues How You'll Grow We are committed to investing and supporting you in your professional development and we have developed a range of programs focused on fostering leadership, growth and development opportunities. We aim to promote continuous learning and individual skills development through on-the-job learning, self-guided professional development courses and certifications. You'll be assigned a dedicated coach to mentor, guide and support you through regular coaching sessions and serve as an advocate for your professional growth.As you progress through your career at FTI Consulting, we offer tailored programs for critical professional milestones to ensure you are prepared and empowered to take on your next role. What You Will Need to Succeed Experience in ideating a proof-of-concept and of independently managing workstreams in larger projects. Experience in mentoring junior resources.Basic Qualifications Bachelor's degree in Math, Physics, Computer Science, Statistics, or equivalent qualifications A couple of years of data science experience Ability to travel to clients and FTI office(s)Technical Platform Requirements Proficiency in the following computing language: Python including in depth knowledge of object-oriented programming and design principles. Proficiency in the following query languages: SQL including strong knowledge of database structure and efficiency. Proficiency in the following version control language: Git Proficiency in any of the following AI/ML frameworks: Huggingface, Torch, Tensforflow, Scikit-Learn, and Spacy Experience in of any of the following additional platforms related to MLOps: MLFlow, dbt, Docker, Kubernetes. Experience with working cloud environments such as AWSTechnical Concept Requirements Experience in any of the following AI/ML topics within a work context: Natural Language Processing (NLP), Forecasting, Clustering, Recommendation Engines, Network Analysis (Graph Theory), and Regressions with the ability to discuss in depth the design decisions. Experience in any of the following AI/ML concepts: Cross Validation, Ensemble Methods, Over/Under Fitting, Accuracy/Precision/Recall, RAG, Agents. Understanding of AI/ML performance measurement best practices including but not limited to how to build and apply a QA/QC framework and knowledge of drift, bias, and fairness. Experience in any of the following computer science concepts: Hashing, Space Complexity, and Parallel Processing (Multiprocessing) Ability to work with Linux/ nix systems, bash scripting, SSH (with some instruction). Experience in a Solution Architect role, with a demonstrated ability to design technical solutions including but not limited to Database Design, ModelOps, and Orchestration. FTI Consulting is an equal opportunity employer and does not discriminate on the basis of race, color, national origin, ancestry, citizenship status, protected veteran status, religion, physical or mental disability, marital status, sex, sexual orientation, gender identity or expression, age, or any other basis protected by law, ordinance, or regulation.

Job Description We Are Accenture Song accelerates growth and value for our clients through sustained customer relevance. Our capabilities span ideation to execution: growth, product and experience design; technology and experience platforms; creative, media and marketing strategy; and campaign, content and channel orchestration. Visit us at: The Role NBA decisioning and marketing automation are becoming critical battlegrounds for clients in telco, media, and financial services - where the volume of customer interactions is high, the cost of a wrong decision is real, and the advantage of getting it right is significant. Rules-based systems and legacy platforms are being challenged by purpose-built, AI-driven solutions. Whilst the outcome of this challenge isn't immediately clear we need someone who can navigate the complex set of options, define, design and optmise solutions for our clients. This is a strategy & delivery role. You will define strategic direction, design solutions, and lead the optimisation of decisioning frameworks and automation solutions for major clients. You bring deep expertise in NBA logic, data science, and decisioning architecture - and the consulting capability to turn complex challenges into working solutions. You look at a decisioning problem, ask what outcome we need, what data we have, and what model will work best design it and coordinate delivery with our offshore and client teams. You spot issues before they become problems, raise them, and solve them. Proactively, not reactively. When something is unclear, you create clarity. When something is broken, you fix it. What You Will Do Decisioning & Data Science Design and implement NBA/NBO decisioning frameworks - eligibility rules, suppression logic, propensity score integration, offer prioritisation, and arbitration Operationalise propensity models, uplift models, CLV scores, and churn predictions into live decisioning frameworks Use value-based decisioning logic - incorporating CLV and long-term customer value into prioritisation, not just short-term conversion Measurement frameworks and optimisation Define feature engineering requirements - knowing which signals, triggers, and contextual features drive predictive power in decisioning Architect real-time decisioning solutions integrating with CRM, CDP, and data platforms Advise on technology selection - purpose-built vs platform, capex vs opex - with a forward-looking point of view Automation & Activation Design automated customer journeys across email, push, SMS, in-app, and web personalisation Design trigger-based, event-driven automation flows that respond to customer behaviour in real time Design integrations with marketing, commerce and service platforms to close the loop between model scores and actions Ensure automation is scalable, auditable, and aligned with consent and data governance requirements Delivery & Leadership Lead technical workstreams end-to-end - from design through to live deployment - owning the outcome throughout Define data input requirements for decisioning and drive data quality issues before they become delivery problems Design end to end decisioning solutions Translate model outputs and complex logic into language non-technical stakeholders can understand and trust Mentor junior team members and build decisioning capability across the practice Contribute to business development - shaping proposals and demonstrating technical credibility in client conversations What You Will Bring Required 5+ years in a decisioning, data science, marketing technology, or customer analytics delivery role Hands-on experience designing and delivering NBA/NBO solutions in a commercial environment Deep understanding of decision logic: suppression, fatigue management, prioritisation, and arbitration Experience with using one or more platforms in a decisioning solution - Pega CDH, Salesforce Marketing Cloud, Adobe Target/AEM/Campaign, Braze, Iterable, or purpose-built solutions Strong working knowledge of predictive modelling for decisioning: propensity, churn, CLV, uplift, and incrementality Experience designing statistically valid champion/challenger and multivariant tests and holdout methodologies Ability to critically evaluate model performance in a business context Experience designing measurement frameworks that prove genuine incremental value SQL proficiency; Python or R for data exploration, model validation, and decisioning diagnostics Hands-on automation experience - trigger-based journeys, event-driven architecture, consent management Solution-oriented and proactive - you define the path forward, raise issues early, and drive progress without being pushed Consulting or client-facing delivery experience is a strong advantage Exposure to GenAI applications in decisioning - personalised content generation, AI-driven offer selection Preferred Experience evaluating purpose-built decisioning solutions and contributing to capex/opex business cases Familiarity with real-time streaming technologies in a decisioning context Awareness of data clean rooms and privacy-preserving analytics for audience targeting Bachelor's or Master's degree in a quantitative, technology, or business-related field Who You Are You are a technical specialist who solves problems and delivers outcomes. You have spent enough time in decisioning systems - the data pipelines, the model outputs, the business logic, the edge cases - to know what makes them work in practice, not just in theory. When a client brings you a challenge, you do not wait for someone else to frame the solution. You get into the data, form a hypothesis, and start moving. You are solution-oriented in the most practical sense: focused on the outcome, not the process. If the approach is not working, you say so and bring an alternative. If the data is not fit for purpose, you define what needs to change and drive that conversation. You take full ownership - if a decisioning framework is underperforming, you diagnose it; if stakeholders are misaligned, you get them aligned. You care about whether it works, not just whether it was built. What's in it for You Our Total Rewards consist of a competitive basic salary, annual performance bonus, opportunities to acquire equity and a wide range of health and wellbeing benefits. These include: 30 days of leave per year plus 3 extra volunteering days for charitable work of your choice Family-friendly and flexible work policies Attractive pension plan with financial wellbeing support and resources Private healthcare insurance plan and Mental Wellbeing support Employee Assistance Programme, Career Development and Counselling A range of generous Parental Leave offerings SNGCR01 Qualification Required - Technical Skills Advanced Python - writing clean, production-grade code, not just scripts (OOP, async, packaging, testing) Generative AI & LLM development - prompt engineering, fine-tuning, RAG pipelines, context window management Agentic AI frameworks - LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflows Machine Learning - model development, training, evaluation, and deployment APIs & backend development - FastAPI, REST APIs, microservices architecture Vector databases & embeddings Cloud platforms - Azure GCP, or AWS; deploying and managing AI/ML workloads at scale Version control & MLOps - Git, CI/CD pipelines, model versioning, monitoring in production Data handling Required - Experience & Mindset Demonstrated end-to-end delivery: problem > build > deployed solution > iteration Strong experience with Generative AI in production - not just experimentation A track record of building working solutions, not just prototypes or proofs of concept Hands-on experience with LLM tooling (Claude, GPT-4, Gemini, or equivalent) Strong analytical and problem-solving skills - you debug fast and think in systems Comfortable working with messy, incomplete requirements and driving clarity through action English fluency and comfort working in global, cross-functional teams Preferred Experience with NLP, computer vision, or multimodal AI models Knowledge of AI safety, guardrails, and responsible AI practices in production Familiarity with Snowflake, Databricks, or similar data platforms Prior experience acting as an AI champion or innovator within a larger organisation Consulting or client-facing delivery experience Bachelor or Master degree in Computer Science, Data Science, Engineering, or related field Key Competencies Solution oriented mentality - sees a problem, starts building, ships, improves Experimental mindset - runs fast tests, learns from failure, iterates without ego Strong execution and delivery orientation Advanced AI engineering and Generative AI expertise Collaborative team player Curiosity and commitment to continuous learning Locations London Additional Information Equal Employment Opportunity Statement All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status . click apply for full job details

Responsibilities Lead the effective and responsible use of AI across ClearBank's software engineering teams. Act as a subject matter expert on AI assisted software engineering practices, tooling, and adoption patterns. Shape how teams embed AI into the SDLC in ways that improve productivity, quality, and developer experience. Drive alignment with stakeholders so AI adoption delivers measurable outcomes rather than anecdotal gains. Champion pragmatic governance that enables progress while meeting regulatory and risk expectations. Influence engineering practices across teams and help build a coherent AI enablement approach across the bank. Master and evaluate AI tooling used in software engineering, including copilots, agentic tools, and workflow integrated capabilities. Collaborate directly with engineering teams to improve how AI is used in coding, testing, review, debugging, and documentation. Introduce new AI tools, techniques, or approaches into the engineering community and support adoption at scale. Define and measure success using indicators such as DORA and flow metrics, adoption and engagement signals, and code quality or operational outcomes. Partner closely with Security, Model Risk, and other stakeholders to keep controls proportionate and non blocking. Occasionally build or extend missing capabilities, including AI driven services, agents, or platform enhancements that integrate into the SDLC. Build relationships with other teams across the bank using AI to share approaches, avoid duplication, and support coherent investment decisions. Coach and guide engineers on effective patterns, helping raise capability across the engineering organisation. Requirements Strong background in software engineering, platform engineering, DevEx, or DevOps. Hands on experience using AI assisted development tools in real engineering environments. Experience influencing practices and improving outcomes across multiple delivery teams. Ability to evaluate tools and approaches based on evidence and business impact, not hype. Strong communication skills, able to explain complex concepts clearly and credibly to a wide engineering audience. Outcome driven and evidence based in decision making. Pragmatic and risk aware, especially within regulated environments. Comfortable operating across ambiguity, rapid change, and emerging technology. Collaborative, empathetic, and focused on enabling others to succeed. Experience integrating AI into CI/CD pipelines, internal developer platforms, or SDLC tooling. Familiarity with engineering productivity and quality metrics. Experience working with governance, security, or risk stakeholders. Exposure to agentic systems or AI driven automation within engineering workflows.

Trusted Connectivity for AI-Powered Dominance.Everfox delivers trusted connectivity to protect the world's most critical environments and safeguard the sensitive data powering decision advantage.Built for mission-critical operations, Everfox protects what matters most by securing how data moves, how users access it, and how threats are neutralized across every domain. We enable mission speed and secure collaboration across networks, domains, and allies, while ensuring the data powering AI and advanced analytics remains trusted and protected.We don't just defend systems; we deliver decision dominance.Our Purpose. Protect what matters most by enabling organizations to operate security in the most complex and high-risk digital environments.Our Vision . To be the most trusted authority in high-assurance cybersecurity, enabling secure collaboration across every domain.Our Belief. Security should never limit mission success - it should enable it.Our Promise. We deliver absolute confidence in environments where failure is not an option.About the role:Everfox is hiring Senior Software Engineer to support our team in London, UK. This role suits a strong senior software engineer who wants to go beyond writing code. You do not need a formal delivery-management background, just solid engineering and an appetite to take on more: design, architecture, coordination, planning and end-to-end delivery. Generalists are welcome. What counts is the quality of your reasoning and problem-solving and how you take on a hard challenge, not the exact languages on your CV. You will split your time between hands-on work on our cross-platform desktop and mobile apps and managing delivery across the end-point software layer of the Everfox Hardsec product line. You will shape and deliver the end-point software that gives users access to our secure browsing and VDI solution, owning its design, development and overall user experience.The work spans Linux and Windows desktop applications and mobile apps on Android and iOS, with a focus on quality, usability and enterprise integration. You will also work closely with our testing lead on release management so that each multi-platform release ships reliably and on time.You will help shape the roadmap, coordinate delivery across our Hardsecsolutions, and work with the stakeholders who depend on this software. The work sits on the critical path and is highly visible, directly supporting the commercial priorities of the business, so what you ship lands quickly with the people who use it.If you enjoy owning hard technical problems end to end while keeping a team aligned and delivering, this role is for you.Location This is a hybrid role in London, UK.Key Responsibilities:EngineeringDesign, implement and maintain features and components for cross-platform desktop and mobile applications, with a focus on reliable, high-quality and highly usable software.Write code primarily in modern C++, and work across other languages as the work requires.Lead the scoping, design and estimating of new software and complex integration tasks, building prototypes to de-risk the harder ones.Use AI tooling to improve development speed and quality.Delivery and managementShape and deliver the roadmap for the end-point software, translating company and product priorities into a plan you own and drive.Plan and coordinate work across a small team of engineers, removing blockers and keeping momentum.Help coordinate delivery across our Hardsec solutions, keeping cross-team dependencies visible and managed.Work with Product Managers, QA, Customer Success, Account Management and other Everfox development teams: translating requirements into well-scoped technicalwork, coordinating delivery, and handling integrations across teams.Test, release and improvementOwn release management for the software, working closely with our testing lead across both manual testing and automated test development.Lead the end-to-end integration and test of the software as a component, including its integrations with hardware, with end-user workflow applications on the remote side, and with enterprise infrastructure such as identity providers.Drive improvements in code maintainability, automation and supportability, championing code review, automated testing, stable APIs and the use of AI tooling and agentic workflows.Technical leadershipProvide technical leadership on projects, steering design choices, solving technical issues and guiding others on code quality and testing.Mentor the engineers in your team, set clear objectives, and support their development towards their longer-term goals.Key Knowledge and Skills:• A degree in Computer Science, Engineering, or a related technical or scientific subject.Experience developing complex software in modern C++ for systems software and desktop or mobile applications.Design and architecture experience, and the ability to solve systems-level problems with multiple complex interactions between components, including planning for failure.A strong grasp of core computer science concepts: concurrency, IPC, networking, security including software exploitation, performance and algorithms.A genuine appetite to take on delivery responsibility, even without a formal delivery management background.Nice to haveA proven ability to manage delivery: planning, prioritisation, and keeping stakeholders informed.A track record of coordinating work across more than one team and keeping cross-team dependencies under control.Java or Kotlin, including Android app and NDK/JNI development, and iOS development in Swift or Objective-C.An understanding of usability, user experience and application design.Experience with the Qt framework.CI/CD experience with tooling such as GitLab, Docker and Kubernetes, and Python for automation and testing.Familiarity with modern AI development tooling and agentic workflows.Line-management experience. The role may include line-managing one or more developers depending on team shape, but the core of the job is engineering and delivery.A passion for technology, shown through project work, professional roles or personal projects, and someone who enjoys technical challenges and delivering results.Self-motivated, flexible and adaptable, and able to cope when thrown in at the deep end.Understands the importance of planning, prioritization and getting work done on schedule.Strong interpersonal and communication skills, and the ability to collaborate with and lead others.Empathy, and a habit of open communication and effective feedback.Can own products and features independently, from inception to delivery, while bringing others along rather than delivering solo.A reasonable estimate of the base salary range for this role is:£76 500.00 GBPThe actual salary offered may vary within the range based on a candidates' unique experience, locale, and business needs. In addition to base salary and either bonus or commission, Everfox offers a generous benefits package including competitive annual leave, pension match, PMI, dental, health cash plan, income protection, in a hybrid work environment. Our Talent Acquisition team will provide specific information regarding salary and benefits offerings. Don't meet every single qualification? Studies show people are hesitant to apply if they don't meet all requirements listed in a job posting. If there is something slightly different about your previous experience, but it otherwise aligns and you're excited about this role, we encourage you to apply. You could be a great candidate for this or other roles on our team.Everfox is an equal employment opportunity employer and complies with all applicable federal, state, and local laws prohibiting discrimination. Everfox does not discriminate against any employee or applicant based on race, color, religion, sex, age, national origin, disability, veteran status, marital status, medical condition, or any other category protected by applicable law. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access the Company's career webpage as a result of your disability. You may request reasonable accommodations by sending an email to .Applicants must have the right to work in the location to which you have applied.

Job Description Applied AI Forward Deployed Engineer - Associate Manager London Career Level 8 Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People, Client Value Creation, One Global Network, Respect for the Individual and Integrity. Year after year, Accenture is recognized worldwide not just for business performance but for inclusion and diversity too. "Across the globe, one thing is universally true of the people of Accenture: We care deeply about what we do and the impact we have with our clients and with the communities in which we work and live. It is personal to all of us." - Julie Sweet, Accenture CEO Deliver production quality work - Build and ship AI applications inside client systems, ensuring solutions meet enterprise requirements for performance, security, and reliability. Develop technical assets - Create reusable, production ready artefacts including MCP servers, sub agents, agent orchestration frameworks, and evaluation tooling that can be deployed across client workflows. Support enterprise deployments - Play a key technical role in rollouts of frontier AI capabilities, ensuring smooth integration with existing IT infrastructure and processes. Accelerate adoption - Work shoulder to shoulder with client engineering and product teams to drive meaningful AI adoption, removing blockers and closing skill gaps in real time. Identify patterns and scale - Recognise repeatable deployment patterns across engagements and contribute those insights back to Accenture's I&E FDE practice and our model provider partners to continuously improve our delivery playbook. Maintain cutting edge expertise - Stay ahead of the curve on LLM capabilities, agentic frameworks, evaluation methodologies, and the AI product development ecosystem. Potentially helping to define the learning path for others as the area grows Build strong relationships - Develop trusted working relationships with client teams and AI ecosystem partners, proactively contributing to new opportunities for AI value creation throughout the engagement lifecycle. Represent Accenture in the field - Champion responsible, safe AI deployment and uphold Accenture's standards in every client interaction. Qualification Experience 4 6 years of experience in a technical role with client facing or consulting exposure - Software Engineer, Solutions Engineer, technical consultant, or equivalent. Experience contributing to the delivery of production applications with real business impact, ideally in enterprise environments. Practical experience working with large language models (ideally in a enterprise or start up setting): prompt engineering, agent development, RAG pipelines, evaluation frameworks, workflows, and deployment. Technical Skills Solid programming proficiency (we are open to any experience but primary languages include: TypeScript and the JavaScript ecosystem, Python and Java). Hands on experience building and deploying AI agents or multi agent systems. Working familiarity with enterprise IT architecture, cloud platforms (AWS, Azure, GCP), and system integration patterns. Consulting & Client Skills High agency; comfortable navigating ambiguity, working across complex organisations, and contributing without a well defined playbook. Strong communication skills; able to participate in technical discovery, support stakeholder alignment, and translate AI concepts for non technical audiences. Collaborative mindset with the ability to balance competing priorities while maintaining integrity and a team first approach. Preferred Domain exposure in media, or another enterprise vertical. Familiarity with AI safety, responsible AI frameworks, or enterprise AI governance. Familiarity with AI deployment infrastructure and MLOps tooling. Locations London Additional Information Equal Employment Opportunity Statement All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. Accenture is committed to providing veteran employment opportunities to our service men and women. Please read Accenture's Recruiting and Hiring Statement for more information on how we process your data during the Recruiting and Hiring process. About Accenture We work with one shared purpose: to deliver on the promise of technology and human ingenuity. Every day, more than 775,000 of us help our stakeholders continuously reinvent. Together, we drive positive change and deliver value to our clients, partners, shareholders, communities, and each other. We believe that delivering value requires innovation, and innovation thrives in an inclusive and diverse environment. We actively foster a workplace free from bias, where everyone feels a sense of belonging and is respected and empowered to do their best work. At Accenture, we see well being holistically, supporting our people's physical, mental, and financial health. We also provide opportunities to keep skills relevant through certifications, learning, and diverse work experiences. We're proud to be consistently recognized as one of the World's Best Workplaces . Join Accenture to work at the heart of change. Visit .

Technical Product Manager - Data Manufacturing Infrastructure Location London Business Area Data Ref # Description & Requirements Bloomberg runs on data. In Data, we are transforming how that data is manufactured, observed, validated, and prepared for use by clients, internal systems, and AI-driven products. Our data manufacturing infrastructure supports the pipelines that move content from acquisition through classification, validation, enrichment, modeling, and publication. As those workflows become more automated and AI-enabled, we need infrastructure that is observable, measurable, resilient, and designed for continuous improvement. Data Management & Operations (DMO) is looking for a Technical Product Manager to help shape the next generation of data manufacturing infrastructure. This role will partner closely with DMO, partner Engineering Infrastructure, AI, and domain teams to define a product roadmap for infrastructure capabilities that support automation, observability, process analysis, semantic data readiness, and scalable production workflows. This is not a traditional project management role. You will apply product discipline to infrastructure: translating complex methodological, operational, and Engineering needs into a clear and articulate roadmap; helping teams make explicit tradeoffs; and ensuring that infrastructure design decisions support the long-term strategy for data manufacturing optimization and automation. We'll trust you to: Define and maintain the product roadmap for data manufacturing infrastructure in partnership with DMO and Engineering leadership, ensuring priorities are clear, defensible, and aligned to Data's goals and strategy. Prioritize needs across multiple stakeholders to construct a coherent backlog that reduces complexity and achieves focus. Balance competing infrastructure needs, including observability, pipeline analysis, and technical migrations. Possess a robust knowledge of data manufacturing approaches across Data, and develop strategies that improve adoption while respecting Engineering architecture and operational constraints. Evaluate where agentic and LLM-based approaches add value in the data manufacturing pipeline, and where deterministic microservices, rules engines, APIs, or other traditional implementations remain the better solution. Partner with Engineering on new pipeline components to ensure added intelligence does not reduce observability, diagnosability, maintainability, or operational resilience. Maintain a clear view of technological trends and evaluate open source or third party software that may support the data manufacturing process. Help ensure the observability platform evolves beyond technical event monitoring into an operational intelligence layer that supports analysis, experimentation, simulation, and continuous improvement. Develop a structured interface between Engineering and internal stakeholders, structuring conversations to be well-scoped, technically grounded, and actionable. Shape inbound demand to Engineering, helping stakeholders articulate needs in a way that is complete, prioritized, and consistent with the platform direction. Communicate the Engineering roadmap and platform capabilities to DMO, AI, and domain teams so they can plan their own work with greater confidence. Drive incremental, reversible delivery. You will help define maintainability criteria, release gates, and post-incident learning loops so that edge cases and failures are fed back into product requirements. You'll need to have: Please note we use years of experience as a guide, but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role. 8+ years of experience, including substantial experience in technical product management for infrastructure, platform, data pipeline, or production-scale systems. Experience building product management practice in environments where it did not previously exist, including earning credibility with senior engineers before exercising influence. Technical fluency across microservices architecture, distributed systems, APIs, data pipelines, and platform design. Experience translating ambiguous business, operational, or analytical needs into clear product requirements and Engineering-ready specifications. Experience defining observability, telemetry, or operational intelligence requirements as part of product design, not only as post-deployment monitoring. Strong judgment about when to use AI, LLM, or agentic approaches and when simpler deterministic designs are more appropriate. Strong written communication skills, including the ability to produce clear product requirements, decision memos, roadmap narratives, and senior leadership updates. Proven ability to lead through influence across cross functional or matrixed teams where formal authority is limited or absent. A track record of building trust with technical teams through partnership, clarity, and disciplined prioritization. We'd love to see: Experience with data platforms, ETL/ELT systems, data contracts, schema governance, data quality tooling, metadata management, or lineage platforms. Familiarity with process analytics, statistical process control, workflow simulation, experimentation, or other methods used to evaluate operational systems. Experience defining infrastructure or data product requirements for AI and LLM consumption, including structured and unstructured content workflows. Exposure to data observability tools, lineage systems, or operational monitoring platforms, including a point of view on where these tools succeed and where they fall short. Experience working with semantic models, knowledge graphs, entity resolution, metadata governance, or AI ready data initiatives. Academic or professional background in computer science, data engineering, statistics, economics, operations research, or a related technical discipline. You'll be successful in this role if you: Improve the velocity and variety of content that is ingested by Data and converted into robust data products. Improve the Data's ability to adopt relevant, emerging technologies, as well as pivot to new or differently structured data products. Build credibility with engineering by demonstrating technical depth, judgment, and respect for architectural ownership. Help DMO, Engineering, AI, and domain teams converge on a shared roadmap for data manufacturing infrastructure. Turn observability and instrumentation from a monitoring function into a product capability that supports better decisions. Make infrastructure priorities more visible, adoption paths clearer, and tradeoffs easier for senior stakeholders to understand. Improve the organization's ability to evaluate automation opportunities empirically rather than relying on intuition, one-off analyses, or disconnected tooling. Does this sound like you? Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law. Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email

Senior Data Management Professional - Data Product Owner - (Data AI) Location: London Business Area: Data Ref #: Overview Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock - from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology - quickly and accurately. We apply problem-solving skills to identify workflow efficiencies and implement technology solutions to enhance our systems, products, and processes. Our Team: Data AI contributes to the building of Bloomberg's AI-enhanced products at scale by curating model training data and enhancing how our internal processes use AI. We provide evaluation and annotation frameworks connecting natural language processing and human judgment in order to elevate the quality, intelligence, and usability of the data that drives our products. By investing in AI at a strategic level, we expand our practice of engaging with AI to one that is embedded across Data. Our internal processes to take advantage of new AI technologies and strengthen Data's role in providing robust domain expertise and influential data artifacts to Bloomberg's products. As a result our clients will continue to have high quality data and access to new types of datasets. Responsibilities The Data Product Owner serves as the strategic leader responsible for transforming business operations through data and AI. By aligning product, engineering, and operational partners around a shared vision, they define and deliver the data capabilities that enable intelligent automation, operational scale, and continuous improvement. This role goes beyond managing requirements to shape how the organization uses data as a strategic asset. Through workflow optimization, process simplification, and the thoughtful application of AI, the Data Product Owner drives solutions that increase efficiency, improve quality, and create sustainable business value. Success in this role is measured by the organization's ability to operationalise data and AI at scale, turning complex business challenges into streamlined, reliable, and measurable outcomes. We'll Trust You To Own and evolve scalable frameworks and sophisticated strategies for instruction and evaluation task design, ensuring datasets remain fit-for-purpose for complex Generative AI behaviors Align data frameworks and evaluation strategies with overarching product objectives to guarantee trustworthy, consumable intelligence that supports actionable user decisions Act as the primary multi-functional liaison, driving alignment between Product, Engineering, and Data teams to translate technical complexities into actionable insights Partner with multi-functional teams to define product-aligned requirements and reusable evaluation rubrics, ensuring outcomes meet rigorous Data Quality standards Drive the strategic evolution of our evaluation infrastructure by pioneering reusable, automated frameworks that consistently accelerate multi-functional product delivery You'll Need to Have Bachelor's degree or equivalent experience in Finance, Business, Economics, Accounting, STEM or degree-equivalent qualifications A minimum of four years of demonstrated experience in data management concepts, including data quality, modeling, and random sampling Extensive experience using data visualization tools such as Tableau or Qlik Sense to communicate sophisticated results to partners in a clear, concise manner Demonstrable experience in Data Profiling/Analysis using tools such as Python, R, or SQL Past project/experience analyzing financial datasets or demonstrable experience working on financial market concepts A logical approach to problem-solving with the ability to resolve complex annotation and data-architectural challenges Keen interest in and familiarity with generative AI frameworks and the requirements of Agentic AI Excellent stakeholder management and project leadership skills, with a demonstrable ability to evaluate design trade-offs and seamlessly translate technical complexities between Engineering, Product, and Data teams. Experience in data management concepts such as data quality, data modeling, and data engineering Preferred Qualifications DAMA CDMP or DCAM certifications Experience in using Bloomberg Data, Bloomberg Terminal, and/or enterprise financial data products Interest in solving problems and developing data-driven methodologies for high precision & high recall anomaly detection Past project experience using Agile/Scrum methodologies to manage complex data lifecycles Experience customizing or developing annotation interfaces using Javascript or HTML Please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role. Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law. Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email

Who are we? Equinix is the world's digital infrastructure company , shortening the path to connectivity to enable the innovations that enrich our work, life and planet. A place where bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future. Help us challenge assumptions, uncover bias, and remove barriers-because progress starts with fresh ideas. You'll find belonging, purpose, and a team that welcomes you-because when you feel valued, you're empowered to do your best work. Job Summary Equinix Incubation builds agentic systems that support the software delivery lifecycle end to end through specialized AI agents, human oversight, and enterprise-grade governance. As a Principal Engineer, you will provide technical leadership for the architecture, design, and implementation of critical platform and agent capabilities. This is the most senior individual contributor role within the organization and is responsible for solving complex technical challenges, establishing engineering standards, and influencing the technical direction of the platform. This role may focus on either the Agent Platform & Orchestration domain or the Agent Engineering domain, depending on business needs. Regardless of assignment, you will serve as a technical leader, mentor, and trusted advisor across engineering teams. Responsibilities Architecture and Technical Leadership Design scalable, secure, and reliable architectures supporting agent orchestration, agent-to-agent communication, tool integration, event-driven workflows, and enterprise platform integration. Lead the resolution of complex technical challenges related to reliability, performance, scalability, evaluation frameworks, and operational excellence. Develop and review critical platform and application code, ensuring adherence to software engineering best practices. Provide technical guidance and architectural direction across multiple engineering teams. Influence the technical strategy and long-term architecture of the platform. Engineering Excellence and Quality Define engineering standards, evaluation methodologies, guardrails, release criteria, and quality frameworks for agent-based systems. Establish observability, monitoring, and evaluation capabilities that enable measurable and repeatable quality outcomes. Review and approve key technical designs and architectural decisions. Promote engineering rigor through technical reviews, documentation, and standards adoption. Ensure technical quality, maintainability, and operational readiness across platform and agent capabilities. Platform and Product Delivery Partner with product management and engineering leadership to translate business objectives into technical strategy and execution plans. Create reusable frameworks, patterns, and reference implementations that accelerate platform development and adoption. Drive continuous improvement of platform capabilities, reliability, operational efficiency, and developer experience. Balance technical innovation with business priorities, delivery timelines, and operational requirements. Technical Mentorship and Influence Mentor and develop engineers through technical coaching, design reviews, and knowledge sharing. Foster adoption of engineering standards, best practices, and platform patterns across teams. Influence technical decision-making through expertise, collaboration, and leadership without direct authority. Build engineering capability by promoting high standards of technical excellence and craftsmanship. Security, Governance, and Operations Ensure platform designs incorporate security, privacy, compliance, auditability, and responsible AI considerations. Partner with security, governance, and architecture stakeholders to meet enterprise requirements. Drive operational excellence through monitoring, resilience, capacity planning, cost optimization, and incident readiness. Champion secure-by-design and reliable-by-design engineering practices across the platform. Qualifications Required Extensive software engineering experience with a proven record of technical leadership across multiple teams and organizations. Deep experience designing, building, and operating distributed systems, cloud-native platforms, APIs, and event-driven architectures. Hands on experience building and delivering LLM powered applications, AI systems, or agent based solutions in production environments. Strong software development expertise in Python, TypeScript, or comparable modern programming languages. Demonstrated experience establishing technical standards, engineering practices, and architectural direction at scale. Proven ability to mentor senior engineers and develop technical talent. Strong written and verbal communication skills with the ability to influence technical and business stakeholders. Preferred Qualifications Experience with agent frameworks, orchestration platforms, and protocols such as MCP, A2A, LangGraph, Bedrock, Vertex AI, OpenAI, Anthropic, or similar technologies. Experience building developer platforms, orchestration engines, SDLC tooling, or engineering productivity solutions. Experience implementing enterprise AI systems within regulated or security conscious environments. Experience with responsible AI governance, evaluation frameworks, and model quality practices. Contributions to open source software, technical publications, patents, or industry conference presentations. Equinix Values At Equinix, we operate with a growth mindset and embrace diversity of thought and contribution. We are committed to creating an environment where everyone can do their best work, grow their careers, and contribute to our success. We welcome people with diverse experiences and backgrounds who are passionate about solving complex technical challenges and building technology that creates meaningful business impact. Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form. Equinix is an Equal Employment Opportunity and, in the U.S., an Aff irmative Action employer. All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law. We use artificial intelligence in our hiring process. Learn more here. This posting is a new position within our organization.

About us One team. Global challenges. Infinite opportunities. At Viasat, we're on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We're looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team. What you'll do Our team builds data-driven products that directly drive Viasat's revenue growth bytransforming how our commercial and customer-facing teams operate. We createinnovative data and software tools that sales, account management, and customersuccess teams use to close more deals, retain customers, and deliver better customerexperiences. As Senior Solutions Architect, you'll co-lead the technical architecture anddevelopment of our entire platform ecosystem: web portals, automated documentgeneration systems, and cloud applications that process billions of records. You'llcollaborate on end-to-end technical decisions, from selecting frameworks to designingintegrations between BigQuery data pipelines, Salesforce, and enterpriseauthentication systems. Working in Python, AWS Lambda, Next.js/React, andTerraform, you'll architect high-performance solutions while mentoring teammembers and contributing innovative ideas for future capabilities. Your technical decisions directly influence how hundreds of commercial and customer-facing professionals across global business units identify prospects, prioritize opportunities, retain accounts, and deliver differentiated customer experiences. A key part of the role is evaluating and integrating emerging AI capabilities - including LLM-powered features, AI agent frameworks, and MCP servers - to accelerate both internal tooling and customer touchpoints. You'll join an existing Senior Solutions Architect and share technical ownership of theplatform, dividing focus across features and initiatives. You'll work with AnalyticsEngineers in your team who build the data pipelines powering your applications,sales teams across business units who provide direct feedback, product andcommercial teams who understand customer needs as well as data engineers and ITteams who help scale solutions. This cross-functional exposure gives you uniqueperspective on both technology and business context. You'll help scale successful,well-loved tools from MVP stage to enterprise-grade platforms serving new markets,working in a small, collaborative team with startup pace but enterprise resources andmandate. The day-to-day You'll architect new applications and features across the full stack, from designingAPI endpoints and service architectures to implementing frontend interfaces. Dailywork involves reviewing technical designs with Analytics Engineers, making architectural decisions on system integrations, and writing code in Python andTypeScript to implement solutions from infrastructure through user interface. A typical day includes conducting proof-of-concepts for new tools and technologies,evaluating their fit for the platform architecture, and presenting technicalrecommendations to the team. This increasingly includes AI-powered capabilities: evaluating LLM APIs (such as Anthropic Claude or OpenAI), building MCP servers toexpose internal data to AI agents, and prototyping agentic workflows that automaterepetitive commercial processes. You'll investigate and resolve production bugs,optimize web portal performance and rendering efficiency, debug Lambda functions,and refactor components to improve reliability and maintainability. You'll designefficient data movement patterns in the cloud to handle high-volume datasets andensure applications remain responsive under load. You'll collaborate with the Product Lead to define technical requirements for newfeatures, propose implementation approaches, and estimate development effort. Thisincludes designing integration patterns between systems, implementingauthentication and authorization systems for enterprise portals, specifying APIcontracts, and selecting scalable technologies that can grow with the platform. You'llalso spend time on infrastructure work: deploying services via Terraform,configuring CI/CD pipelines, architecting document generation systems, and ensuringapplications meet performance and security requirements for enterprise deployment. What you'll need Expert-level Python development experience building production applications Expert-level AWS experience, including Lambda, ECS/Fargate, S3, and APIGateway Proven experience deploying and managing containerized applications usingDocker Strong SQL skills and experience working with data warehouses Hands-on experience with Infrastructure as Code tools, particularly Terraform Proficiency with Git and modern CI/CD workflows Demonstrated ability to design and implement multi-component softwaresystems from architecture through production deployment Experience making technical architecture decisions and trade-offs in fast-paced environments What will help you on the job Experience with modern web development frameworks, particularly Next.js,React, and TypeScript Familiarity with Google Cloud Platform services, especially BigQuery andCloud Run Knowledge of enterprise authentication patterns including SSO, SAML, OAuth,and RBAC Experience processing and optimizing applications that work with high-volume datasets at scale Background in B2B SaaS, sales enablement tools, or CRM platforms Track record of scaling MVPs into enterprise-grade platforms Experience working in Agile environments using tools like JIRA Comfort working across the full stack from infrastructure to frontend Ability to mentor junior engineers and establish technical best practices Understanding of how technical decisions impact business outcomes and useradoption Experience with automated document generation or data visualizationlibraries Experience working with LLM APIs (e.g. Anthropic Claude, OpenAI) andbuilding AI-powered features in production applications Familiarity with the Model Context Protocol (MCP) or AI agent frameworks fortool-augmented LLM workflows Understanding of customer lifecycle touchpoints beyond sales - e.g.onboarding, customer success portals, and self-service tooling EEO Statement Viasat is proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, ancestry, physical or mental disability, medical condition, marital status, genetics, age, or veteran status or any other applicable legally protected status or characteristic. If you would like to request an accommodation on the basis of disability for completing this on-line application, please click here.

Why work for us? A career at Janus Henderson is more than a job, it's about investing in a brighter future together. Our Mission at Janus Henderson is to help clients define and achieve superior financial outcomes through differentiated insights, disciplined investments, and world-class service. We will do this by protecting and growing our core business, amplifying our strengths and diversifying where we have the right. Our Values are key to driving our success, and are at the heart of everything we do: Clients Come First - Always Execution Supersedes Intention Together We Win Diversity Improves Results Truth Builds Trust If our mission, values, and purpose align with your own, we would love to hear from you! Your opportunity Janus Henderson is undertaking a firm-wide AI transformation programme to embed AI capabilities across every business function and become the most technologically sophisticated asset manager in the world. The AI Academy has already been established with a focus on helping users consume AI inside M365. Our next major expansion is enabling the firm's builders - engineers, architects, product owners, analysts, data engineers, quants, and platform specialists - to encode AI into the way technology is delivered and operated. The AI Business Partner for Builders will design and run this expansion. You will define the curriculum, stand up the cohort model, and partner across Technology, Investments, and Innovation to ensure all builders are utilizing modern AI tooling with broad knowledge sharing on best practices and organizational knowledge on the latest developments in AI deployment. You will also work closely with Percepta and the technology organization to extend the program into maximizing the AI-native application development occurring on JHOS. This is not a purely a training role or governance role. It sits at the intersection of hands on technical credibility, program design, and change enablement - helping builders work differently and accelerate our AI transformation. This will include directly engaging with builders on specific high priority projects, and then extending that learning and knowledge to the rest of the community. You will report into the Head of Innovation and operate within the AI Academy framework alongside the AI Business Partner team, sharing infrastructure, governance, comms, and the firm wide adoption dashboard. Your primary toolkit today spans the modern AI engineering stack - coding agents, agentic harnesses, MCP, in platform AI in Snowflake and Databricks, and the JHOS / NEXUS platform Percepta is building - but the firm's AI strategy is platform agnostic. You will be expected to evaluate, learn, and deploy new tools as the landscape evolves. Design and run the Builders curriculum: a general foundation for all builders (tools, models, agentic patterns, cross persona level setting) and role specific tracks for app engineers, data engineers, architects, security, product owners, and analysts Design and lead the Builders cohort - the technologist equivalent of Air Traffic Controllers - running them through the material first, iterating with their feedback, and equipping them to cascade training through their teams Partner with Percepta and the Technology org to design Phase 3: enabling engineers to build AI native applications on the JHOS platform, including agent orchestration, governance, and the NEXUS workspace Run hands on, workshop style sessions grounded in participants' real sprint work covering coding agents, agentic CI/CD, planning with LLMs, spec writing and verification, long running agents, and team level skill sharing (CLAUDE.md, SKILLS.md, shared prompt libraries). Partner with Technology, Security, and Architecture to resolve adoption blockers - acceptable use guidance, access paths, budget signals, approved tools - so builders know what is sanctioned and can experiment with confidence Develop and implement appropriate metrics within the AI Academy framework: pipeline telemetry (deploy frequency, lead time, change failure rate, time to restore), survey based signals (focus time, perceived effectiveness), and adoption data across GitHub Copilot, AI Foundry, APIM, Cortex, Databricks Genie Code, and the forthcoming LLM Gateway Stay current with the rapidly evolving AI engineering landscape - coding agents, agentic harnesses, MCP, model releases, benchmarks, DORA and industry research - and translate what matters into practical curriculum changes Collaborate with Technology, Security, and Responsible AI teams to ensure curriculum, tools, and patterns taught are aligned with the firm's governance, data privacy, and compliance posture Carry out other duties as assigned What to expect when you join our firm Hybrid working and reasonable accommodations Generous Holiday policies Excellent Health and Wellbeing benefits including corporate membership to Wellhub Paid volunteer time to step away from your desk and into the community Support to grow through professional development courses, tuition/qualification reimbursement and more Maternal/paternal leave benefits and family services All employee events including networking opportunities and social activities Lunch allowance for use within our subsidized onsite canteen Must have skills Hands on engineering credibility. You have shipped software, and you currently use modern coding agents (GitHub Copilot agent mode, Claude Code, OpenCode, or equivalent) on real work. You can sit down with a senior engineer, pair on their codebase, and add value within the hour Working fluency with the modern AI engineering stack - agentic harnesses, MCP, repo level context (CLAUDE.md / SKILLS.md), agentic CI/CD patterns, long running agents, and the tradeoffs between line completion, agent mode, and orchestrated multi agent workflows Curriculum design and facilitation experience - you have built and run technical training, workshops, or enablement programmes for engineers and other technologists, and you know the difference between a session people endure and one they apply on Monday morning Strong cross persona communication. Equally credible with a staff engineer debating verification strategy, a product owner rewriting a spec for an agent, an architect worried about review throughput, and an SLT sponsor asking about ROI Practical change management instincts. You understand that tools and training are only half the job; surfacing and removing adoption blockers - access, acceptable use, budget, fear - is the other half Business analysis and measurement literacy. Comfortable with DORA metrics, SPACE, developer experience research, and the difference between adoption (a prerequisite) and value (the goal). You can design a survey, interpret pipeline telemetry, and avoid vanity metrics Self directed and comfortable with ambiguity. This effort is brand new; you will define how it runs, with sponsorship but without a detailed playbook Strong documentation instincts. You produce reusable curriculum, patterns, and playbooks that outlast your direct involvement and can be picked up by cohort members and other Academy leads Experience working in a regulated environment (financial services, healthcare, legal, government) where governance, compliance, and data sensitivity shape how tools are evaluated, approved, and deployed Nice to have skills Direct experience in financial services or asset management, particularly exposure to investment technology, quant platforms, trading systems, or data engineering in a regulated context Experience building or operating AI native applications - agent orchestration, retrieval systems, evaluation pipelines, LLM application architecture Familiarity with the Janus Henderson Technology stack or analogous environments: Azure AI Foundry, APIM fronted LLM gateways, Snowflake Cortex, Databricks Genie Code, GitHub Enterprise, Jira / ServiceNow workflows Familiarity with the JHOS / NEXUS platform direction or comparable internal AI platforms built on top of foundation models Background in developer experience, platform engineering, or internal tooling - where success is measured by other engineers' productivity, not your own commits Experience leading a community of practice, internal guild, or cohort based enablement programme Product management sensibility - MVPs, iteration, user feedback, prioritisation - applied to curriculum and enablement rather than software features Familiarity with DORA research, SPACE, Accelerate, and current industry thinking on AI's impact on the software development lifecycle Public contributions - talks, writing, open source - that demonstrate ongoing engagement with the AI engineering community Supervisory responsibilities No - but you will lead the Builders effort and develop cohort members, equipping them to facilitate within their own teams Potential for growth Leadership development programs Regular training Career development services Continuing education courses Microsoft AI, GitHub, Anthropic, and cloud platform certification pathways Exposure to a firm wide AI transformation programme with direct executive visibility Opportunity to shape a new function - the Tier 3 lead role is being established for the first time at Janus Henderson . click apply for full job details