39 jobs found

AI Architect (Generative & Agentic AI) Permanent Location: London (onsite twice a week) Salary: £80,000 - £95,000 Per Annum D.O.E Plus benefits & Bonus Shape the next generation of enterprise AI We're looking for a senior AI Architect to lead the design and delivery of cutting-edge Generative and Agentic AI solutions across complex enterprise environments. This is a client-facing, strategic role for someone who combines deep technical expertise with strong consulting instincts, someone who can move comfortably between vision, architecture, and real-world delivery. You'll work on high-value transformation initiatives, helping organisations turn AI from experimentation into measurable business impact. The Role: As an AI Architect, you'll operate at the intersection of strategy, solution design, and delivery. You will: Lead discovery and design of AI-led solutions aligned to business outcomes Architect and scale GenAI, RAG, and Agentic AI systems in production Advise senior stakeholders on AI strategy, feasibility, and roadmap Act as a technical authority during bids, proposals, and client workshops Guide engineering teams through complex implementations This role offers real ownership, from shaping ideas through to deploying production-grade AI platforms. Key Responsibilities: Client & Stakeholder Engagement Partner with commercial and delivery teams to qualify opportunities and shape compelling AI propositions Act as a trusted advisor in workshops, discovery sessions, and solution design discussions Support RFI/RFP responses and client presentations with clear, credible technical direction Solution Architecture & Delivery Design enterprise-ready Data & AI architectures using modern cloud platforms (AWS, Azure, GCP) Architect RAG-based GenAI solutions, chatbots, and autonomous/agentic workflows Select appropriate models, frameworks, orchestration tools, and evaluation approaches Ensure solutions are secure, scalable, observable, and production-ready Technical Leadership & Innovation Lead and mentor teams of AI and software engineers Drive best practices across MLOps / LLMOps, governance, and AI observability Contribute to reusable accelerators, reference architectures, and go-to-market offerings What We're Looking For: Essential Experience & Skills: Proven experience architecting solutions across Generative AI, Agentic AI, ML, and automation Strong understanding of: Prompt engineering RAG pipelines Model fine-tuning (supervised / unsupervised) MLOps / LLMOps and AI observability Hands-on experience building enterprise RAG solutions using LLMs (e.g. OpenAI, Llama, Mistral, Claude) and vector databases (Pinecone, Weaviate, FAISS, etc.) Practical experience with GenAI frameworks such as LangChain, LlamaIndex, and agentic frameworks like AutoGen, CrewAI, LangGraph Strong Python expertise with AI/ML frameworks (PyTorch, TensorFlow) and NLP libraries Experience deploying AI solutions on at least one major cloud platform (AWS, Azure, or GCP) Solid software engineering foundations for building scalable, maintainable systems Experience leading or guiding teams of AI / software engineers Consulting & Communication: Strong stakeholder management and communication skills Comfortable translating complex AI concepts into clear business value Experience supporting proposals, bids, and client presentations Why Apply? Work on meaningful, enterprise-scale AI transformation programmes Shape AI strategy and architecture, not just build proofs of concept High visibility, senior-level role with real influence Continuous exposure to modern AI tooling, frameworks, and delivery models Strong investment in learning, innovation, and professional development

AI Engineer (Generative & Agentic AI) Permanent Location: London (onsite twice a week) Salary: £75,000 - £85,000 Per Annum D.O.E Build intelligent systems that solve real enterprise problems: We're looking for an AI Engineer who wants to do more than just plug into APIs, someone who wants to own the build, shape intelligent systems, and bring advanced GenAI and Agentic AI solutions into real-world production. If you're motivated by tackling messy enterprise problems, not just experimenting with models, this is a role where you'll build systems that genuinely change how organisations operate. Why this role exists: Enterprises are past the experimentation phase. They're asking harder questions: How do we make GenAI stable, scalable, and safe? How do we move from prototypes to production? How do we integrate AI into existing products and workflows? You'll be the engineer who takes these questions and turns them into working, impactful AI systems, not just research pieces or demo-ware. This role is ideal for someone who thrives on building, iterating, and owning AI solutions end-to-end. The Role: As an AI Engineer, you'll be responsible for designing, building, and deploying production-grade AI systems in complex enterprise environments. You will: Build and deploy GenAI, RAG, and Agentic AI systems that solve real business challenges Develop robust pipelines, services, and integrations that turn models into usable products Work across front-end, back-end, and data layers to deliver complete, functioning AI solutions Collaborate with architects, data scientists, and product stakeholders to shape solutions and define delivery paths Take ownership of performance, scalability, and maintainability of AI components Continuously experiment, improve, and bring new ideas forward, without heavy process slowing you down This isn't a research role and it's not "keep the lights on." It's product-driven engineering where you ship real systems into production. Key Responsibilities: AI System Development Build and optimise AI models and pipelines Implement RAG, agentic workflows, and advanced reasoning techniques Deploy LLM-driven features into real products Full-Stack & Platform Engineering Develop APIs, backend services, data flows, and integration layers Contribute to UI/UX when needed as part of end-to-end delivery Ensure clean, scalable engineering across the stack MLOps / LLMOps Own the deployment, monitoring, and iteration of AI systems Use modern tooling to ensure models and pipelines are reliable, observable, and repeatable Collaboration Work closely with cross-functional teams to identify opportunities and translate them into robust engineering solutions Provide technical input into architecture, design discussions, and delivery planning What We're Looking For: Core Experience: Strong Python engineering skills and experience delivering production AI/ML systems Hands-on experience with LLMs, RAG, vector databases, and GenAI frameworks Experience deploying solutions on cloud platforms (AWS, Azure, or GCP) Familiarity with LangChain, LlamaIndex, or agentic frameworks is highly valuable Strong grounding in software engineering best practices (testing, versioning, CI/CD, scalability) Mindset & Behaviours: Seek ownership, not just tasks Enjoy solving real user and business problems, not just model optimisation Thrive in environments where they can experiment and move quickly Communicate clearly with both technical and non-technical stakeholders Want to see their work in production, being used by real people Why Join? Work on impactful AI programmes that go beyond prototypes Build meaningful, high-value systems that people actually use Work with modern GenAI tools, approaches, and delivery models Collaborate with experienced architects, engineers, and innovators Strong investment in engineering excellence, innovation, and personal development If you want to build AI systems that matter, not just experiment with models, this is your next move.

Artificial Intelligence Architect Salary: Up to £100,000 + Benefits Location: Hybrid - 3 days per week onsite in London Working Hours: 40 hours per week A globally renowned organisation is seeking an Artificial Intelligence Architect to lead the design and delivery of advanced AI solutions across complex enterprise environments. This is a senior, client-facing role combining deep technical expertise with strategic advisory, focused on Generative and Agentic AI, solution architecture and transformation-led outcomes. The role is suited to an experienced AI leader who can operate at both strategic and hands-on levels, shaping AI platforms, guiding stakeholders and delivering scalable, production-grade solutions. Responsibilities for the Artificial Intelligence Architect: Partner with commercial and delivery teams to qualify opportunities, shape proposals and build compelling business cases Act as a trusted advisor during discovery sessions, workshops and bid processes Translate business requirements into enterprise-grade Data and AI architectures Design and architect Generative AI and Agentic AI solutions for operational support, monitoring and business workflows Lead complex AI implementations, ensuring solutions deliver measurable value Evaluate and select appropriate models, frameworks, orchestration tools and platforms Architect and scale LLM-powered applications including chatbots and agent-based systems Produce thought leadership content and contribute to go-to-market propositions Maintain strong awareness of emerging technologies and the competitive AI landscape Collaborate closely with data science, engineering and business teams to design robust end-to-end solutions Contribute to account strategy, aligning technical delivery with business priorities Drive productivity improvements and cost optimisation through intelligent automation Essential Skills for the Artificial Intelligence Architect: Proven experience architecting solutions across Generative AI, Agentic AI, machine learning and automation Strong understanding of prompt engineering, RAG pipelines, model tuning, MLOps and LLMOps Experience delivering enterprise-scale RAG solutions using LLMs and vector databases Ability to design AI platforms that integrate with existing enterprise technology stacks Hands-on experience with core GenAI frameworks and agent-based AI concepts Strong deployment experience on at least one major cloud platform including AI and ML services Solid software engineering foundation for building scalable, maintainable AI systems Advanced Python expertise with AI and ML frameworks Experience with MLOps and LLMOps tooling including containerisation and orchestration platforms Proven experience delivering applications using state-of-the-art LLMs including prompt design, fine-tuning and evaluation Strong understanding of advanced agent architectures, reasoning systems and evaluation methodologies Excellent stakeholder engagement and consulting capability Experience leading and mentoring teams of AI or software engineers If you are an experienced AI Architect looking to shape enterprise AI strategy and deliver cutting-edge solutions within a high-impact environment, please apply in the immediate instance. AI, Artificial Intelligence

We're hiring an experienced AI Platform Engineer to design, build and operate a production-grade Generative AI platform powering next-generation intelligent products. This is a hands-on engineering role focused on taking AI solutions from prototype to scalable, reliable services used in real-world environments. You'll sit at the intersection of DevOps, cloud infrastructure and applied AI owning the full lifecycle of Retrieval-Augmented Generation (RAG) and LLM-powered systems across modern cloud architecture. This role is about engineering, not research. You will architect and run the infrastructure that enables AI to perform securely, reliably and at scale ensuring performance, cost control and operational maturity as adoption grows. You'll work closely with AI engineers, security teams, and product stakeholders to transform experimental models into hardened, production-ready services while shaping a reusable AI platform capable of supporting multiple products. What You'll Be Doing Design and optimise scalable RAG pipelines and vector search systems Orchestrate multi-model AI services with a focus on latency, resilience and performance Productionise GenAI workflows and ensure they operate reliably under real usage Build and run AI services across AWS and Databricks Develop ingestion, embedding and retrieval pipelines Deploy containerised workloads via Kubernetes and Helm Implement Infrastructure-as-Code using Terraform Introduce end-to-end monitoring, tracing and alerting for AI workloads Improve inference and retrieval performance while reducing operational cost Establish fault-tolerant, scalable infrastructure patterns Embed security, evaluation and governance into the AI lifecycle Build CI/CD pipelines and automation to support continuous model deployment Create reusable platform components to accelerate future AI initiatives Strong experience in: Cloud infrastructure engineering (AWS-focused environments) Kubernetes, containerisation, and distributed systems Terraform / Infrastructure-as-Code CI/CD, automation, and platform reliability Running production workloads with high availability requirements Plus, experience with one or more of the following: MLOps or ML platform engineering RAG architectures, embeddings, or vector search Model serving, observability or performance optimisation Data / AI workflow orchestration in Databricks or similar ecosystems Why Join? Work on real-world AI systems operating at scale Own platform design decisions and influence long-term architecture Blend modern DevOps practices with cutting-edge Generative AI use cases Be part of a growing, innovation-driven engineering environment Opportunity to define how AI is operationalised across multiple products If you're excited by building the infrastructure that makes AI usable, scalable and reliable in production, we'd love to hear from you. 49914MS INDLON Portfolio Payroll Ltd is acting as an Employment Agency in relation to this vacancy.

Senior AI Engineer (Customer & Product AI)LondonContractCompetitive day rate2 day per week onsite (preferred)IR35 determination in progress OverviewWe are partnering with a major consumer brand that is scaling AI across multiple markets to improve customer experience, unlock growth, and drive operational efficiency. They are building a central AI team focused on designing, building, and deploying production-grade AI solutions across the business. They are looking for a Senior AI Engineer to lead the delivery of end-to-end AI products, working across software engineering, machine learning, and LLM-based systems. This is a hands-on role focused on shipping real solutions into production that directly impact customers, teams, and commercial outcomes. The RoleYou will join a cross-functional AI function working at the intersection of software engineering, data, and machine learning. Your focus will be on turning business problems into production-ready AI systems, from early discovery through to deployment, monitoring, and continuous improvement. You will work closely with teams across marketing, digital, operations, and product to design and deliver AI-powered features such as personalisation, prediction models, and AI assistants. You will be expected to take ownership of delivery, make pragmatic architectural decisions, and help shape engineering standards across the team. Key Responsibilities Act as a hands-on builder and technical owner of AI-powered products and features from concept through to production Design and deploy end-to-end AI solutions spanning data preparation, modelling, APIs, and production integration Build and optimise ML and LLM-driven services, including prediction models, personalisation, and retrieval-augmented systems Collaborate with business stakeholders to frame problems, define success metrics, and deliver measurable outcomes Develop services, APIs, and integrations that embed AI into customer journeys, internal tools, and digital platforms Own model lifecycle processes including deployment, monitoring, evaluation, and retraining Implement robust MLOps practices to ensure reliability, performance, and scalability Mentor engineers and contribute to shared tooling, reusable patterns, and engineering standards Required Experience Strong software engineering background with Python and SQL Proven experience delivering end-to-end ML or AI solutions into production environments Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn Experience working with LLMs, including prompt design, RAG, or fine-tuning Experience building APIs and integrating AI systems into real products Solid understanding of data pipelines, feature engineering, and model evaluation Experience working with cloud platforms such as Azure, AWS, or GCP Nice to Have Experience in customer analytics, personalisation, recommendation systems, or marketing optimisation Familiarity with Databricks or modern data platform tooling Experience building conversational AI or internal AI assistants Exposure to experimentation frameworks such as A/B testing Experience working in cross-functional product teams Why Apply Build AI products that are used in the real world at scale Work across a broad range of use cases spanning customer experience, operations, and digital platforms Join a growing, central AI function with strong executive backing Opportunity to shape architecture, standards, and long-term AI capability To Apply, Please email:

AI Solutions Architect (Innovation & GenAI) Salary: Up to £120,000 + Benefits Location: Hybrid - 3 days per week onsite in London Working Hours: 40 hours per week A globally established organisation is seeking an AI Solutions Architect to lead the design of innovative, cloud-native AI architectures that support rapid experimentation while maintaining a clear path to enterprise-scale delivery. This is a senior, hands-on architecture role focused on shaping proof-of-concepts, MVPs and scalable AI platforms that deliver tangible business value. The AI Solutions Architect role is suited to an experienced architect who combines deep technical expertise with strategic thinking, enjoys working in fast-moving environments, and can guide teams from early ideation through to production-ready solutions. Responsibilities for the AI Solutions Architect: Design pragmatic, fit-for-purpose architectures for AI PoCs and MVPs that can be delivered within short innovation cycles while remaining production-aware Provide technical leadership during client workshops, discovery sessions and ideation phases, assessing feasibility in real time Develop and maintain reusable reference architectures, patterns and templates to accelerate AI solution delivery Evaluate emerging AI tools, platforms and services, making informed build-versus-buy decisions Design cloud-native architectures using serverless and PaaS services to enable rapid deployment, cost control and scalability Define lightweight integration approaches connecting AI solutions with enterprise data sources, systems and APIs Establish security, governance and compliance standards for rapid AI development, ensuring data protection and responsible use Design AI architectures with clear pathways to production scaling, documenting trade-offs and technical decisions Mentor engineers and developers through architectural guidance, reviews and best-practice sharing Build architectural knowledge across multiple domains to support diverse use cases and enterprise contexts Align solutions with established enterprise standards and architectural principles Essential Skills for the AI Solutions Architect: Strong expertise in Python and JavaScript Hands-on experience with backend frameworks and modern frontend frameworks Deep knowledge of Generative AI and agent-based AI frameworks including RAG and orchestration patterns Strong experience working with vector databases and AI-specific data stores Solid understanding of AI and ML models, LLMs and generative AI architectures Experience implementing governance frameworks for model selection, deployment and lifecycle management Hands-on experience with AI-assisted development tools Strong knowledge of cloud AI and ML platforms and associated architecture patterns Experience designing and managing APIs including REST and GraphQL Strong understanding of microservices and serverless architectures Practical experience with DevOps and MLOps practices including CI/CD pipelines Knowledge of security frameworks, identity management and authentication standards Desirable Skills for the AI Solutions Architect: Experience with enterprise integration patterns and event-driven architectures Exposure to data engineering and data platform architectures Experience with Infrastructure as Code tools If you are an AI Solutions Architect with strong full-stack capability and a passion for delivering enterprise-grade AI solutions, please apply in the immediate instance.

Senior Machine Learning Engineer Up to £120,000 + bonus London based (hybrid 2-3 days per week in office) If you enjoy solving real business problems, and working technical team, this is a brilliant place to grow. You'll work on end-to-end ML projects across multiple private equity companies, helping them unlock value, modernise their data capabilities, and embed production-ready AI and ML solutions. THE COMPANY This technology and consulting organisation partners with private equity firms across the UK and Europe to deliver meaningful, data-driven transformation. With a good technical team they've built a positive reputation and an enjoyable team to work with. THE ROLE As a Senior ML Engineer, you'll work across different clients, industries, and use cases - perfect if you enjoy variety and dislike being stuck on slow moving projects. You'll be hands-on with Python, cloud, and Databricks, building and deploying ML solutions with real commercial impact. You can expect to work on projects such as: Optimisation models Predictive modelling for customer churn, asset failure, or sales performance Full ML life cycle ownership: prototyping ? deployment ? monitoring Building production-ready pipelines, APIs, and MLOps workflows You'll typically work in a small and cross-functional team. SKILLS AND EXPERIENCE The successful Machine Learning Engineer will have the following skills and experience: 4-6+ years in ML Engineering or Data Science Strong Python skills and experience with cloud platforms (AWS, GCP, or Azure) Experience building and deploying production ML systems Familiarity with Databricks, Spark, or MLOps workflows (nice to have but not essential) Solid understanding of modern ML methods and data engineering fundamentals Strong academic background (ideally Russell Group, with a Master's minimum) Ability to work quickly in fast-paced environments and communicate with non-technical stakeholders BENEFITS The successful Machine Learning Engineer will receive the following benefits: Competitive salary based on level Hybrid working Ability to work across multiple industries and projects Extremely strong, and technical team Clear progression paths and high visibility in a small organisation HOW TO APPLY Please register your interest by sending your resume to Madison Barlow via the Apply link on this page.

MLOps Engineer London Based - Hybrid (Three days per week on site)£90,000 to £110,000 plus bonus This is an exciting opportunity to join a mission driven cleantech scale up as they continue to grow their data and AI function. You will help shape a modern MLOps environment, working on impactful machine learning deployments that directly support smarter, cleaner energy systems. The Company They are a fast growing technology scale up within the energy and electric space. The team is collaborative, customer focused, and driven by a strong product mindset. You would be joining a small, high impact data group with experienced engineers and the opportunity to take real ownership. The Role In this MLOps Engineer role, you will contribute to the design, deployment and optimisation of production ML systems. Responsibilities include: Supporting data scientists and AI engineers to build, deploy and monitor ML models in production environments. Managing ML lifecycle Designing scalable ML pipelines for training, validation and deployment. Implementing CI/CD workflows for machine learning and maintaining reliable ML endpoints. Working heavily with AWS, including SageMaker, to deliver robust, secure and scalable ML infrastructure. Applying strong engineering standards across cloud, DevOps and automation practices. Contributing to computer vision and broader ML workloads, with scope to support new AI initiatives as they grow. Your Skills and Experience To succeed, you will bring strong commercial experience in: Python and applied ML engineering. MLOps tooling such as MLflow and modern experiment tracking platforms. Deploying models into production, including monitoring, testing and automation. AWS, with practical experience using SageMaker. Cloud and DevOps foundations including Docker and AWS Building scalable data and ML pipelines with solid engineering practices. You work well in fast paced environments, communicate clearly, and enjoy collaborating with cross functional teams. What They Offer Competitive salary plus discretionary bonus. Hybrid working with three days each week in their London office. A high impact role within a growing data and AI team. Strong ownership, rapid development opportunities and exposure to modern ML tooling. A mission led environment focused on accelerating the transition to clean energy. How To Apply Please register your interest by sending your CV to Madison Barlow via the Apply link on this page.

AI Ops Engineer Salary: Up to £85,000 Location: Hybrid - 3 days per week onsite in Derby Working Hours: Full time - Monday to Friday A globally renowned organisation is seeking an AI Ops Engineer to join a growing AI and data function, taking ownership of the operational backbone that enables AI systems to run reliably, securely and at scale in production environments. This AI Ops Engineer role sits at the intersection of machine learning, cloud infrastructure and DevOps, supporting the full lifecycle of AI solutions from deployment through to ongoing optimisation. The AI Ops Engineer position is well suited to an engineer who enjoys building resilient platforms, improving operational maturity and working closely with data scientists and software engineers to deliver production-grade AI capability. Responsibilities for the AI Ops Engineer: Design, build and operate deployment pipelines for AI models, prompts and supporting artefacts Own lifecycle management including versioning, promotion, rollback and retirement of AI solutions Implement monitoring and observability covering performance, usage, drift and data quality Ensure AI systems meet security, compliance and governance requirements Optimise inference performance, scalability and cost efficiency Manage infrastructure supporting training and inference including cloud platforms, containers and GPU resources Enable reproducibility through experiment tracking and artefact management Support incident response, root-cause analysis and resolution of AI-related failures Collaborate with data scientists and software engineers to design scalable, reliable machine learning infrastructure Develop and maintain CI/CD pipelines for machine learning workloads Maintain standards for version control, testing and technical documentation Work with cross-functional teams to integrate AI solutions into existing platforms and workflows Stay current with advancements in MLOps, DevOps and AI operations, driving continuous improvement Essential Skills for the AI Ops Engineer: Strong experience operating machine learning or AI systems in production environments Hands-on experience with CI/CD pipelines for data or ML workloads Experience managing cloud-based infrastructure for AI workloads Solid understanding of monitoring, observability and operational resilience Strong collaboration skills with the ability to work across engineering and data teams Experience supporting secure, compliant and well-governed systems Desirable Skills for the AI Ops Engineer: Experience integrating Python-based services with modern front-end frameworks Familiarity with MLOps practices for deploying, monitoring and managing AI systems Exposure to large-scale enterprise data environments or knowledge management systems Understanding of Agile delivery practices and collaborative tooling Knowledge of data security, compliance and responsible AI principles Domain exposure within engineering or manufacturing environments If you are an AI Ops Engineer looking to take ownership of AI operations within a complex, production-focused environment, please apply in the immediate instance. AI, Artificial Intelligence

AI Engineer Salary: Up to £80,000 + Benefits Location: Hybrid - 3 days per week onsite in London Working Hours: Full time - Monday to Friday A globally renowned organisation is seeking an AI Engineer to join a high-performing technology function delivering intelligent, production-grade AI solutions across enterprise environments. This is a hands-on role combining full-stack engineering with advanced AI system development, focused on building scalable, secure and impactful solutions that deliver measurable business value. The AI Engineer role suits an experienced engineer with strong software foundations and practical expertise across Generative AI, Agentic AI and machine learning, who enjoys working closely with stakeholders and contributing to complex delivery initiatives. Responsibilities for the AI Engineer: Design, develop and maintain end-to-end AI solutions spanning front-end interfaces, back-end services and data pipelines Build, optimise and deploy AI and machine learning models ensuring solutions are scalable, maintainable and production-ready Deliver Generative AI, Agentic AI and classical machine learning solutions aligned to enterprise requirements Integrate AI systems with existing enterprise platforms ensuring stability and seamless operation Collaborate closely with data scientists, engineers and business stakeholders to identify opportunities and deliver robust solutions Provide technical guidance and mentorship to junior engineers, promoting best practice across AI development Lead implementation of engineering standards across AI and ML delivery Stay current with emerging AI technologies and contribute to continuous innovation Essential Skills for the AI Engineer: Strong proficiency in Python with extensive experience using AI, ML and NLP libraries Hands-on experience working with modern large language models including prompt engineering, fine-tuning and evaluation Practical experience with core Generative AI frameworks and agent-based AI frameworks Strong experience with MLOps and LLMOps tooling including model lifecycle management Proven deployment experience on major cloud platforms including AI and ML services Solid foundation in software engineering principles for scalable, production-grade systems Experience designing and delivering enterprise AI solutions including RAG-based architectures using vector databases Proven experience delivering full-stack AI or ML systems within enterprise environments Strong understanding of advanced agent architectures, reasoning systems and autonomous workflows Excellent communication and stakeholder management capability Experience supporting proposals, client-facing discussions or technical presentations If you are an AI Engineer with strong full-stack capability and a passion for delivering enterprise-grade AI solutions, please apply in the immediate instance. AI, Artificial Intelligence

Job Title: Automated Intelligence SME (SC CLEARED) Target Start Date: ASAP Target End Date: Six months from start Recruitment Type: Contractor Rate: £600+ per day inside IR35 Location: Hybrid (travel may be required to Basingstoke and Bracknell) Clearance Required: active SC Clearance is mandatory (minimum six months' validity) Working Pattern: Monday to Friday Role Overview: We are seeking an experienced Automated Intelligence Subject Matter Expert to support a major secure-sector programme in the design, implementation and delivery of Automated Intelligence capabilities. This role requires strong technical expertise, stakeholder management and a deep understanding of automation, AI/ML integration and secure-environment delivery. Key Responsibilities: Design and Development Design, build and deploy automation solutions integrating AI/ML models into existing systems and workflows. Process Analysis: Work with business stakeholders and subject matter experts to identify automation opportunities and define technical and functional requirements. Coding and Programming: Develop automation scripts and build pipelines for data ingestion, preprocessing and feature engineering using languages such as Python, Java or R. Testing and Maintenance: Conduct thorough testing, resolve issues, monitor accuracy and system performance, and implement updates or improvements as needed. Collaboration: Partner with cross-functional teams including data scientists, engineers, software developers and IT operations to ensure seamless integration of AI/automation solutions. Documentation and Reporting: Produce and maintain clear technical documentation and prepare performance reports, insights and recommendations for further optimisation. Required Skills and Experience Technical Skills: Strong proficiency in programming languages such as Python, Java, C# or R. Experience with machine learning frameworks and libraries (e.g. TensorFlow, PyTorch, Scikit-learn). Familiarity with cloud platforms (AWS, Azure or Google Cloud) and MLOps practices. Knowledge of automation technologies including RPA platforms (e.g. UiPath) and orchestration tools (Airflow, Kubeflow). Soft Skills: Excellent problem-solving and analytical capabilities. Strong written and verbal communication skills. Effective stakeholder management, with the ability to liaise between technical and non-technical teams. Adaptability and a commitment to continued learning in a rapidly evolving technology landscape. Security Requirements: Active SC Clearance in place is required for this role. Single UK National with no caveats. Willingness to undergo higher-level security clearance as required.

About The Role FDM is looking for a Machine Learning Engineer to work with one of our clients in the Insurance sector. The successful candidate will join a transversal Data team, playing a key role in transforming and modernising the organisation's machine learning platform. This role involves collaborating across the business to define and implement MLOps best practices, as well as designing, building, and maintaining the infrastructure required for developing and deploying machine learning models. This is initially a 6 month contract with the potential to extend and will be a hybrid role based in Reading. The Machine Learning Engineer will work closely with data scientists, data engineers, solution engineers, and a range of stakeholders to ensure seamless integration of machine learning models into production systems, driving innovation and operational excellence within the client. Responsibilities: Contribute to the design and the development of robust MLOps, and Agentic Ops frameworks that will enhance our capabilities and drive value across the company. Take offline models data scientists build and turn them into a real machine learning production system. Define and implement best practices in Machine Learning, MLOps, and Agentic Ops, while mentoring colleagues throughout the organisation. Actively participate in knowledge sharing through internal and external communities and working groups. Contribute to the delivery of code and provide expertise in several key technology areas. Stay up to date with the latest advancements in MLOps, Agentic systems, Azure and Databricks technologies, and proactively identify opportunities to enhance our ML capabilities. About You Degree in computer science, engineering, or proven experience in ML engineering. Proven experience in building and operating machine learning models. Experience in multiple technologies and frameworks required such as Azure Databricks, Azure ML, MLFlow, GIT, Python and PySpark and microservices. Strong understanding of software development, DevOps, MLOps and Agentic Ops practices and microservices. Excellent communication and collaboration skills. About Us We are a business and technology consultancy and one of the UK's leading employers, recruiting the brightest talent to become the innovators of tomorrow. We have centres across Europe, North America and Asia-Pacific, and a global workforce of over 3,500 Consultants. FDM has shown exponential growth throughout the years, firmly establishing itself as an award-winning employer and is listed on the FTSE4Good Index. Diversity and Inclusion FDM Group is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, national origin, age, disability, veteran status or any other status protected by federal, provincial or local laws. Why join us Career coaching, mentoring and access to upskilling throughout your entire FDM career Assignments with global companies and opportunities to work abroad Opportunity to re-skill and up-skill into new areas, develop non-linear career paths and build a skillset within your field Annual leave and work-place pension

Senior DevOps Pre-Sales Solutions Engineer Solutions Engineer UNITED KINGDOM Senior DevOps Pre-Sales Solutions Engineer - London (Hybrid - 3 days per week in the office) - UNITED KINGDOM Are you a high-impact DevOps Pre-Sales professional who thrives at the intersection of deep technical expertise and enterprise sales? Do you already operate in a customer-facing DevOps pre-sales role - leading technical wins, running proof-of-concepts, and shaping complex DevSecOps conversations at enterprise level? If yes, this could be your next major career move. About the Company: Our client is a leading global software platform transforming how modern organisations build, secure, and deliver software across DevOps, DevSecOps, and MLOps environments. Trusted by thousands of enterprises worldwide - including many of the world's largest organisations - their platform plays a mission-critical role in securing and accelerating software delivery from code to production. This is not a small-scale vendor role. This is software supply chain at global enterprise level. Strict Requirement - Who This Role Is For This opportunity is ONLY open to professionals who: Are currently working in a DevOps Pre-Sales / Solutions Engineering role Have a strong hands-on DevOps technical background Have personally led technical evaluations, POCs and technical wins Are comfortable operating in complex enterprise sales cycles This is not : A pure DevOps engineer role A post-sales Customer Success role A generic Solutions Architect role A role for someone trying to "move into pre-sales" You must already be operating successfully in DevOps-focused technical pre-sales. The Role As Senior Solutions Engineer, you will act as a trusted technical advisor to strategic enterprise customers . You will own the technical strategy from first conversation through to successful proof-of-value and technical close. You will: Partner with enterprise customers to design secure software supply chain architectures Deliver compelling deep-dive technical presentations and live demonstrations Lead and own end-to-end proof-of-concept engagements Drive the technical win in complex enterprise sales cycles Design and size solutions based on customer environments Deliver technical enablement to customers and partners Represent the company at industry events Provide structured customer insight back to Product & Engineering This is high-visibility, high-impact, and highly strategic. What You Must Bring Experience: 5+ years in Solutions Engineering / DevOps Pre-Sales / Technical Sales Demonstrated success owning technical wins in enterprise environments Minimum 2.5-year average tenure per employer DevOps Technical Depth (essential): CI/CD pipeline architecture and integrations Git-based platforms (GitHub, GitLab, Bitbucket) DevSecOps tooling and security integrations SCA, SAST, SBOM management Container security Strong understanding of modern cloud and distributed systems Highly desirable: Background in software development Exposure to MLOps You must be equally credible in front of: Heads of DevOps Platform Engineering teams Security leaders C-level technical stakeholders Why This Role Stands Out Global enterprise exposure Complex, intellectually challenging sales cycles Cutting-edge DevSecOps and software supply chain technology High-calibre peer group Strong career progression potential This is a role for professionals who enjoy being the most technically credible person in the room - while also influencing major commercial decisions. If you are an experienced DevOps Pre-Sales Solutions Engineer ready to step into a more strategic, enterprise-focused environment, I'd be very interested in speaking with you IND123

Role Summary We are seeking a highly skilled MLOps Engineer to focus on the deployment, monitoring, and maintenance of machine learning models in production environments. This role is platform-focused and does not involve model development or end-user support. The successful candidate will ensure reliability, scalability, and performance of ML platforms while managing API endpoints and deployment workflows. Key Responsibilities Platform Operations & Monitoring Monitor ML model endpoints and platform health using tools such as Grafana and Domino Data Lab Respond to incidents and alerts; perform code fixes and manage changes via ServiceNow Liaise with Domino Data Lab support to resolve platform-related issues Model Deployment Deploy and maintain ML models in production environments Ensure models integrate seamlessly into automated pipelines Maintain reliability, version control, and governance standards Pipeline Maintenance Collaborate with Data Scientists and Engineers for smooth production handoff Maintain and optimize ML pipelines for stability and scalability Improve performance, resource usage, and automation Automation & Tooling Implement automation for deployment and monitoring Contribute to continuous platform improvements Required Skills & Experience Strong Python programming experience Proven experience deploying and monitoring ML models in production Understanding of model evaluation metrics, data drift, overfitting, and feature importance Experience with AWS services (S3, Redshift, etc.) Hands-on experience with Grafana for monitoring Familiarity with Domino Data Lab (desirable) Strong knowledge of CI/CD, version control, Docker, Kubernetes Excellent troubleshooting and incident management skills Strong stakeholder communication skills

Lead Data Engineer/Head of Data Permanent On behalf of a fantstic cleint we are resourcing for the following role This is a senior, hands-on technical leadership role reporting directly to the CTO. You'll shape and deliver a modern data and AI platform, lead a small team of data and analytics engineers, and embed machine learning, AI agents, and advanced analytics into real customer workflows. The Role You'll own the end-to-end data and AI capability - from platform architecture through to production ML systems - ensuring data and AI are applied thoughtfully, responsibly, and with clear business impact. What You'll Do Design and evolve a secure, scalable data & AI platform with Snowflake at its core Build production-grade data pipelines, models, and data products for analytics and AI use cases Design, train, and deploy ML models, embeddings, and vector stores to enable AI-driven experiences Lead and mentor a small, high-impact team of data and analytics engineers Partner closely with Product, Engineering, and Infrastructure teams Set standards for data quality, governance, security, and performance Act as a trusted technical advisor to the CTO and senior leadership What We're Looking For Essential Expert-level Snowflake experience (modelling, optimisation, advanced features) Strong Python skills across data engineering, ML, and AI development Proven experience delivering production ML systems Hands-on experience with embeddings, vector databases, and LLM-driven systems Deep understanding of modern data engineering practices (ELT, orchestration, versioning) Nice to Have Background in data science or applied ML Experience building AI agents or intelligent automation Familiarity with cloud-native architectures and MLOps

Analytics Platform Engineer (Python, Kubernetes) - Secure Gov - Cheltenham - (RL8096) Job Title - Analytics Platform Engineer (Principle & Senior) Location - Cheltenham Salary - Competitive Benefits - Bonus and commission scheme, comprehensive benefits package including private medical and pension, flexible hybrid working, clear progression with funded training, and enhanced long-term incentives including additional leave and retention bonuses. Work on analytics platforms that support highly sensitive, mission-critical programmes within a secure environment. This is an opportunity to build and scale modern data platforms while contributing to projects of national significance, alongside some of the strongest engineers in the sector. The Client - We're partnering with a leading organisation in the secure government sector to support the growth of a key programme delivering advanced data and analytics capabilities. This is a critical hire within an expanding team, focused on building and scaling platforms that underpin mission-critical solutions. Operating at the forefront of data, cloud, and AI-driven innovation, they offer an environment where engineers can work on complex, high-impact challenges with real-world significance. The Candidate - This would suit a candidate with a strong background in data or analytics platform engineering, who is comfortable working across both software development and infrastructure. You'll enjoy solving complex technical challenges, working in dynamic environments, and collaborating closely with Data Scientists and MLOps teams. A pragmatic, adaptable mindset is key, along with a passion for building scalable, secure systems that enable data-driven outcomes. You should also be comfortable working in secure, highly regulated environments. The Role - We are seeking Senior and Principal Analytics Platform Engineers to join a growing team delivering high-impact solutions within a secure environment. You will play a key role in designing, building, and evolving a modern analytics platform, supporting the full life cycle from development through to deployment and ongoing optimisation. This is a hands-on role offering exposure to a broad and evolving technology landscape. Due to the nature of the work, you will be operating within a highly secure environment with specific access requirements. Key Duties: Design, build and evolve scalable analytics and data platforms Contribute across the full software development life cycle Support cloud migration and data management initiatives Develop, test and deploy new platform capabilities Troubleshoot and enhance existing analytics services Provide hands-on support to Data Scientists and MLOps teams Tackle complex engineering challenges across a varied tech stack Requirements: Strong experience with Python Experience with Kubernetes and Docker Understanding of CI/CD pipelines (eg GitLab) Exposure to data platforms, MLOps or machine learning environments Desirable: Spark or Scala AWS services (eg S3) Elasticsearch or graph databases Vector databases/modern data tooling OIDC/OAuth Node.js or React To apply for this Analytics Platform Engineer permanent job, please click the button below and submit your latest CV. Curo Services endeavours to respond to all applications, however this may not always be possible during periods of high volume. Thank you for your patience. Curo Services is a trading name of Curo Resourcing Ltd and acts as an Employment Business for contract and temporary recruitment as well as an Employment Agency in relation to permanent vacancies.

We're hiring an experienced AI Platform Engineer to design, build and operate a production-grade Generative AI platform powering next-generation intelligent products. This is a hands-on engineering role focused on taking AI solutions from prototype to scalable, reliable services used in real-world environments. You'll sit at the intersection of DevOps, cloud infrastructure and applied AI owning the full lifecycle of Retrieval-Augmented Generation (RAG) and LLM-powered systems across modern cloud architecture. This role is about engineering, not research. You will architect and run the infrastructure that enables AI to perform securely, reliably and at scale ensuring performance, cost control and operational maturity as adoption grows. You'll work closely with AI engineers, security teams, and product stakeholders to transform experimental models into hardened, production-ready services while shaping a reusable AI platform capable of supporting multiple products. What You'll Be Doing Design and optimise scalable RAG pipelines and vector search systems Orchestrate multi-model AI services with a focus on latency, resilience and performance Productionise GenAI workflows and ensure they operate reliably under real usage Build and run AI services across AWS and Databricks Develop ingestion, embedding and retrieval pipelines Deploy containerised workloads via Kubernetes and Helm Implement Infrastructure-as-Code using Terraform Introduce end-to-end monitoring, tracing and alerting for AI workloads Improve inference and retrieval performance while reducing operational cost Establish fault-tolerant, scalable infrastructure patterns Embed security, evaluation and governance into the AI lifecycle Build CI/CD pipelines and automation to support continuous model deployment Create reusable platform components to accelerate future AI initiatives Strong experience in: Cloud infrastructure engineering (AWS-focused environments) Kubernetes, containerisation, and distributed systems Terraform / Infrastructure-as-Code CI/CD, automation, and platform reliability Running production workloads with high availability requirements Plus, experience with one or more of the following: MLOps or ML platform engineering RAG architectures, embeddings, or vector search Model serving, observability or performance optimisation Data / AI workflow orchestration in Databricks or similar ecosystems Why Join? Work on real-world AI systems operating at scale Own platform design decisions and influence long-term architecture Blend modern DevOps practices with cutting-edge Generative AI use cases Be part of a growing, innovation-driven engineering environment Opportunity to define how AI is operationalised across multiple products If you're excited by building the infrastructure that makes AI usable, scalable and reliable in production, we'd love to hear from you. 49914MS INDLON Portfolio Payroll Ltd is acting as an Employment Agency in relation to this vacancy.

Automated Intelligence SME Clearance Required: SC An opportunity is available for an experienced AI Subject Matter Expert to support the implementation and delivery of Automated Intelligence solutions within secure environments. You will work across technical and business teams to design, develop and deploy AI enabled automation capabilities that integrate into existing enterprise systems. The Role You will support the delivery of AI driven automation initiatives across secure programmes. The position requires strong technical capability combined with stakeholder engagement and risk awareness. Key Responsibilities Design, build and deploy automation solutions integrating AI and machine learning models into existing systems and workflows. Analyse business processes with stakeholders to identify automation opportunities and define clear requirements. Develop automation scripts and build data pipelines covering ingestion, preprocessing and feature engineering. Conduct testing, troubleshooting and performance monitoring to maintain system accuracy and reliability. Collaborate with data scientists, software engineers and IT teams to ensure seamless deployment. Produce clear technical documentation and performance reporting. Support contract discussions, stakeholder engagement and business risk considerations where required. Technical Skills Required Proficiency in programming languages such as Python, Java, C# or R. Experience with machine learning frameworks including TensorFlow, PyTorch or Scikit-learn. Familiarity with cloud platforms such as AWS, Azure or Google Cloud and associated MLOps practices. Experience with automation and orchestration tooling such as UiPath, Airflow or Kubeflow. Experience and Capability Strong experience delivering AI or automation solutions within enterprise environments. Ability to work with cross functional teams and translate technical solutions into business value. Experience operating within controlled or regulated environments. Strong written and verbal communication skills. Experience supporting stakeholder engagement and business risk management. This role suits a technically credible AI professional who can design and implement automation solutions while engaging effectively across secure and regulated programmes. To apply, please send your CV by pressing the apply button

Data & AI Automation Lead Data, AI, Automation, Machine Learning, Transformation, Global B2C organisation London Hybrid Immediate OIR35 Contract - longer term permanent opportunity A market-leading global B2C organisation is seeking a Data & AI Automation Lead to own and scale its enterprise AI and intelligent automation agenda. This is a high-impact leadership role responsible for defining AI strategy, building production-grade AI/ML and automation capabilities, and delivering measurable commercial value across customer experience and operations. The Role Define and execute the enterprise AI & automation roadmap Identify high-value use cases (personalisation, dynamic pricing, forecasting, workforce optimisation) Own AI/ML platforms, MLOps and LLM architecture (Azure preferred) Lead end-to-end delivery from experimentation to scaled deployment Build and lead a multi-disciplinary AI team Embed responsible AI, governance and cost control The Profile Proven track record delivering enterprise-scale AI/ML and intelligent automation Strong hands-on knowledge of cloud AI platforms, data engineering and LLM/RAG architectures Experience implementing MLOps, observability and model governance Commercially minded, able to link AI outcomes to revenue, efficiency and customer impact Background within consumer-led / B2C environments is essential This is a rare opportunity to shape and scale AI capability within a complex, customer-centric international business. If you're ready to lead AI from strategy through to real-world impact, we'd love to speak with you. Data & AI Automation Lead