19 jobs found

Senior Software Engineer (Generative AI Platform) - 6-Month Contract - £650/day (Outside IR35) Location: Europe (Remote-first) Rate: £650/day Duration: 6 months (high likelihood of extension) A cutting-edge engineering team is building a next-generation GenAI platform that empowers autonomous software-engineering agents and fully agentic workflows - and they're looking for exceptional engineers to join them. If you want to work at the forefront of AI , in a space evolving daily, and help define how engineering teams across the world write and ship code in the future this is the contract for you. What You'll Be Working On Designing and developing Go (Golang) services powering a scalable GenAI engineering platform. Building autonomous AI software-engineering agents capable of coding, reasoning, and executing tasks end-to-end. Developing agentic workflows that enable multi-step planning, orchestration, evaluation, and self-improvement. Working in environments like Claude and Cursor to prototype, fine-tune, and deploy AI-for-coding tools. Collaborating with a highly technical, fast-moving team working on projects that support a large, multinational tech ecosystem. What We're Looking For Strong Go (Golang) development experience - production systems, performance, concurrency. Proven background in AI for coding (eg, agent frameworks, LLM-powered tooling, AI code generation, or workflow automation). Hands-on experience developing or integrating with LLM-based systems (Claude, Cursor, OpenAI, etc.). Experience with distributed systems, microservices, or platform engineering. Comfortable working in a fast-paced, experimental environment where the tech evolves every week. Why This Contract Is Exceptional You'll work in a brand-new domain where breakthroughs happen constantly - no Legacy, no stagnation. You stay plugged into the bleeding edge of GenAI , engineering automation, and LLM-powered development. You'll shape systems used across a massive, high-traffic global organisation. Opportunity to influence architecture, agent design, and AI-driven engineering workflows. Be part of a team pushing the boundaries of what software engineering will look like in the next decade. Who Should Apply? We're prioritising experienced contractors based in Europe (outside the UK) with deep engineering and AI exposure who want to join a pioneering initiative in the GenAI engineering space. Interested? Send your profile or reach out directly - this is one of the most forward-thinking engineering contracts available in the EU market right now.

Position: Data & AI Scientist Location: London, UK (Hybrid-3 days a week from office) long term contract position Program Scope: Developing and provisioning of infrastructure that support agentic workflows across both Azure and GCP Data science expertise to help shape the agentic solution design of Coach AI as well as target state AI Assistant Creation of agent integration patterns to fulfil and action on behalf of customers by leveraging Bank systems Development of new AI products for the Conversational Banking Lab, including but not limited to: Agent summarisation - bespoke features to summarise nuanced conversations App search evolution - transforming the existing vector search functionality into a fully generative experience and transition to single experience point Evaluation methods - continued automation of both deterministic and generative conversations in a scaled and simulated way Key Skills/Knowledge: Data & AI Scientist Must haves Python literacy - min 2years+ working on production grade LLM based applications AgenticAI - Langgraph, ADK, CrewAI, multi-agent architectures - experience in building deployable solutions, not jupyter notebooks AI Engineering - RAG pipelines, prompt engineering, VertexAI experience, LLMOps and runtime evaluation/monitoring Nice to haves Responsible AI - strong understanding of AI ethics, risks and mitigations incl. guardrail development • Exposure to Agile/Scrum methodologies.

Position: ML & AI Engineer Location: London, UK (Hybrid-3 days a week from office) long term contract position Program Scope: Developing and provisioning of infrastructure that support agentic workflows across both Azure and GCP Data science expertise to help shape the agentic solution design of Coach AI as well as target state AI Assistant Creation of agent integration patterns to fulfil and action on behalf of customers by leveraging Bank systems Development of new AI products for the Conversational Banking Lab, including but not limited to: Agent summarisation - bespoke features to summarise nuanced conversations App search evolution - transforming the existing vector search functionality into a fully generative experience and transition to single experience point Evaluation methods - continued automation of both deterministic and generative conversations in a scaled and simulated way Key Skills/Knowledge: ML & AI Engineer Must haves Python literacy - min 2years+ working on production grade LLM based applications Software Engineering - strong understanding of microservices architecture, CI/CD pipelines, event driven architecture AI Engineering - RAG pipelines, prompt engineering, VertexAI experience, LLMOps and runtime evaluation/monitoring Data engineering - scaled data pipelines using python/spark. GCP native services: BQ, Spanner, Dataflow, Firestore Nice to haves AgenticAI - Langgraph, ADK, CrewAI, multi-agent architectures - experience in building deployable solutions, not jupyter notebooks Data ontologies - graphical approaches to data storage + retrieval Exposure to Agile/Scrum methodologies

Job Title: AI Engineer / Data & AI Scientist (LLM, Generative AI, Python) We are recruiting for an AI Engineer / Data & AI Scientist to join a high-impact programme building next-generation conversational AI and generative AI platforms. This role focuses on developing production-grade LLM applications, agent-based AI systems and RAG pipelines used in large-scale customer-facing environments. This is an opportunity to work on advanced AI assistant and conversational AI technology, building scalable multi-agent architectures and generative search systems using modern AI frameworks. Key Responsibilities Design and build LLM-powered applications using Python and Generative AI frameworks Develop RAG (Retrieval Augmented Generation) pipelines and AI orchestration workflows Build and deploy agent-based AI systems using tools such as LangGraph, CrewAI or similar frameworks Engineer scalable AI infrastructure across Azure and GCP environments Implement prompt engineering, model evaluation and LLMOps monitoring Develop AI products including conversational AI assistants, summarisation tools and generative search capabilities Required Skills Strong Python development experience Experience building production LLM or Generative AI applications Knowledge of RAG pipelines, prompt engineering and vector search Experience with agentic AI frameworks (LangGraph, CrewAI or similar) Exposure to LLMOps, model evaluation or monitoring Experience with cloud AI platforms such as Azure AI or Vertex AI (GCP) Desirable Experience Conversational AI or AI assistant platforms Multi-agent architectures Responsible AI, AI ethics or guardrail design Agile / Scrum environments This is an excellent opportunity for an AI Engineer, Machine Learning Engineer, LLM Engineer or Generative AI Engineer looking to build production AI systems and next-generation conversational AI platforms. Apply now to work on cutting-edge generative AI and LLM technologies.

Applied AI Software Engineer - LangChain, LangGraph, RAG, Knowledge Graphs A high-growth, technology-led scale-up (backed by a global leading organisation) is expanding its engineering capability following a highly successful 2025. As part of significant continued investment, they are hiring a Software Engineer to lead the design and development of next-generation AI products and services across Finance, supporting both internal operations and external platforms. This is an opportunity to work in a modern, cloud-native engineering environment, building intelligent agentic AI systems that can reason, plan and act autonomously. You will take ownership of solutions end-to-end; from design and architecture, through development and deployment, to optimisation and continuous improvement. You'll work closely with engineering, product and platform teams to embed Agentic AI and LLM-driven workflows into real-world products, contributing to architectural decisions, engineering standards and best practices. Location: Remote with twice a month travel to Leeds / Bradford Salary: £90,000 to £110,000 + 15% Bonus + Excellent Benefits To be considered Strong experience as an AI Engineer / ML Engineer / Software Engineer with applied AI exposure. Hands-on Python development experience delivering production-grade systems. Practical experience building agentic AI workflows (LangGraph / LangChain or similar frameworks). Exposure to Knowledge Graphs (Neo4j / RDF / graph-based enrichment or retrieval). Experience integrating LLM APIs (OpenAI or similar), with prompt design and orchestration. This is an excellent opportunity for a senior developer to build impactful Agentic AI systems, influence technical direction, and work within an organisation that is actively investing in AI as a core capability.

Job Description: Cybersecurity Consultant (Cloud, Data, AI & Microsoft Security) Department: Information Security - (Data & AI team) Duration: Duration 4 months Location : London (Hybrid) Role Overview We are looking for a highly skilled Cybersecurity Consultant with strong expertise across Microsoft Security , Cloud Security , Data Protection , and emerging AI/LLM security and governance . The role focuses on identifying security gaps, defining secure-by-design patterns, supporting product and platform teams, and strengthening enterprise security posture-particularly across Microsoft 365, Azure, data platforms, and AI-enabled solutions. You will play a key role in threat modelling, risk assessments, guardrail design & implementation, and delivering practical security guidance for engineering, data, and application/product teams. Rationale/deliverables: Contribute to the Operating Securely program by providing information security advice and support to product and engineering teams and validate that security controls are in place and issues / vulnerabilities remediated Perform technical risk assessments for proposed new and changing systems, including products that are designed and built by the client as well as the secure deployment and configuration of business applications that report on and analyse data, e.g. Power BI Perform technical risk assessments and advise product and engineering teams on the secure implementation of AI based solutions, e.g. autonomous AI agents, LLMs, LRMs, and AI-enhanced productivity systems Support the roll-out of the new AI information security control framework Support the Data governance team Key Responsibilities Perform threat modelling (STRIDE), guardrail definition, and security posture assessments across applications, data platforms, APIs, cloud services, and SaaS ecosystems. Identify security control gaps , especially around data pipelines, repositories, network security, API security, middleware, and cloud architectures. Conduct technical security risk assessments , produce risk statements/reports, and support teams with remediation and mitigation strategies. Develop security controls, standards, and documentation for product teams, platform engineering, and data services (e.g., pipelines, warehouses, data sources). Provide expert guidance on Microsoft Security Stack , including: Microsoft Defender (XDR, MDE, MDI) Microsoft Entra ID (SSO, MFA, Conditional Access, PIM) Microsoft Purview (DLP, Information Protection, Data Governance, DSPM) Microsoft 365 Copilot & GitHub Copilot security enablement Partner with data governance, platform engineering, DevOps, and architecture teams to embed secure-by-design Support secure adoption of cloud-native technologies (Azure), DevSecOps pipelines, GitOps practices, and GitHub Advanced Security (GHAS). Oversee security controls for cryptography, key management, secrets management, HSM/Key Vault configurations , and cloud network security (firewalls, proxies, segmentation). Drive secure integration of AI/LLM tools , including Copilot, Azure OpenAI, and agentic systems-ensuring proper guardrails, risk assessments, and data protection. Participate in cloud monitoring, detection & incident response , working with SIEM/XDR tooling and platform/application teams. Collaborate closely with data governance to ensure appropriate classification, labeling, access control, and lifecycle management of sensitive data. Essential Skills & Experience Strong understanding of security frameworks (CIS), MITRE ATT&CK, and AI/LLM security frameworks. Hands-on experience with Azure cloud security , DevSecOps, and cloud-native architectures. Expertise with Microsoft 365 Security and Azure Security Strong knowledge of IAM (SSO, MFA, Conditional Access, AAD/Entra, PIM). Experience delivering data security , DLP, DSPM, and governance controls using Microsoft Purview. Practically skilled in AI security , including risk identification, secure integration patterns, and AI governance models. Experience with cloud monitoring, incident response, SIEM/XDR operations. Ability to translate complex security risks into clear business language and actionable recommendations. Desirable Skills Experience with secure data platforms (Azure Data Factory, Data Lake, SQL, or similar). Knowledge of API, container security, Kubernetes, and infrastructure-as-code security. Familiarity with PCI, GDPR, data privacy requirements, and compliance frameworks. Exposure to adaptive protection, insider risk management, and automated DLP frameworks. Personal Attributes Strong communicator able to work across engineering, data, product, and business teams. Highly analytical with a structured approach to problem-solving. Comfortable in fast-paced environments undergoing modernization and AI adoption. Ability to influence teams and drive secure-by-design culture across the organization

PRINCIPAL AI PLATFORM ENGINEER Up to £90,000 + BENEFITS SHEFFIELD (Hybrid) This is a standout opportunity to shape and scale an AI function from the ground up. You will drive the build of production-grade AI platforms, develop agentic automation for complex workflows, and deliver real business impact in an environment where engineering decisions directly influence performance and efficiency. THE COMPANY: They are a technology-led insurance organisation. Their products are powered by a combination of smart technology and human expertise, enabling them to offer fast, tailored cover to customers with diverse needs. With strong investment behind AI, they are entering a new phase of growth and building their first dedicated AI engineering team. Joining at this stage gives you the chance to influence technical strategy, architecture, and best-practice from day one. THE ROLE: Build and operate production-ready AI agents on GCP Design robust RAG pipelines covering ingestion, text processing, vector search and secure data handling. Implement evaluation frameworks, monitoring, A/B testing and performance dashboards for latency, cost and accuracy. Partner with product and operations teams to deploy AI capabilities into live environments and continually optimise performance. Shape engineering standards, patterns and tooling as part of a new AI function. YOUR SKILLS AND EXPERIENCE: Strong commercial experience in Data Engineering, ML Engineering or Software Engineering with applied AI delivery. Deep hands-on expertise with GCP services Strong Python skills Practical experience with LLMs, embeddings, RAG architectures and vector databases. A track record of building production-grade AI systems, including observability, evaluation and automated testing. DevOps capability across CI/CD, Docker and Kubernetes or equivalent tooling. THE BENEFITS: You will receive a salary, dependent on experience. Salary is up to £90,000 On top of the salary there are some fantastic extra benefits. HOW TO APPLY Please register your interest by sending your CV to Molly Bird via the apply link on this page.

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.

Systems Research Engineer About the Company Our client is seeking a Systems Research Engineer to join their AI team in Edinburgh. This is a full-time, permanent role focused on building the next generation of AI-native infrastructure and "Agentic Serving" architectures. Working at the cutting edge of LLM workloads and distributed systems, you will be supported by world-class experts in a high-growth environment. This is a unique opportunity to enter the AI sector, offering an exceptional career path and long-term growth potential. Junior-level candidates are welcome to apply. About the Role Job Title: Systems Research Engineer Location: Edinburgh Who we are looking A Degree in Computer Science / Electrical Engineering, or a related field Proficiency in C/C++ Experience in Python for prototyping Hands-on experience with LLM frameworks Having one of these knowledge areas: distributed systems, operating systems, machine learning systems architecture, Inference serving, and AI Infrastructure Skilled in systems research, distributed algorithms, and performance profiling Junior-level candidates are welcome to apply Pay range and compensation package Competitive salary 33 days annual leave per year (including UK public holidays) Group Personal Pension Life insurance Private medical insurance Medical expense claim scheme Employee Assistance Program (EAP) Cycle to Work scheme Company sports club and social events Opportunities for funded additional professional certifications or training, where relevant to the business Equal Opportunity Statement If you are ready to turn your technical expertise into strategic impact, please send your CV and research portfolio (if any) to Maggie Kwong ( email : (url removed) / mobile : (0)(phone number removed) ) Project People is acting as an Employment Agency in relation to this vacancy.

AI Platform Engineer London Excellent Salary +Benefits Join an award-winning, internationally recognised B2B consultancy as an AI Platform Engineer, owning the cloud-native platform that underpins conversational AI and generative AI products at scale. Sitting at the core of AI delivery, you will design, build, and operate the runtime, infrastructure, and operational layers supporting RAG pipelines, LLM orchestration, vector search, and evaluation workflows across AWS and Databricks. Working closely with senior AI engineers and product teams, you'll ensure AI systems are scalable, observable, secure, and cost-efficient, turning experimental AI into reliable, production-grade capabilities. With further scope of responsibilities detailed below: Own and evolve the AI platform powering conversational assistants and generative AI products. Build, operate, and optimise RAG and LLM-backed services, improving latency, reliability, and cost. Design and run cloud-native AI services across AWS and Databricks, including ingestion and embedding pipelines. Scale and operate vector search infrastructure (Weaviate, OpenSearch, Algolia, AWS Bedrock Knowledge Bases). Implement strong observability, CI/CD, security, and governance across AI workloads. Enable future architectures such as multi-model orchestration and agentic workflows. Required Skills & Experience Strong experience designing and operating cloud-native platforms on AWS (Lambda, API Gateway, DynamoDB, S3, CloudWatch). Hands-on experience with Databricks and large-scale data or embedding pipelines. Proven experience building and operating production AI systems , including RAG pipelines, LLM-backed services, and vector search (Weaviate, OpenSearch, Algolia). Proficiency in Python , with experience deploying containerised services on Kubernetes using Terraform . Solid understanding of distributed systems, cloud architecture, and API design , with a focus on scalability and reliability. Demonstrable ownership of observability, performance, cost efficiency, and operational robustness in production environments. Why Join? You'll own the foundational AI platform behind a growing suite of generative AI products, working with senior AI leaders on systems used by real customers at scale. This role offers deep technical ownership, long-term impact, and an excellent compensation package within a market-leading organisation. INDAMS Portfolio Payroll Ltd is acting as an Employment Agency in relation to this vacancy.

AI Engineer Location: Remote with Adhoc travel to site (London or Birmingham) Contract Length: 6 Months Working Pattern: Full Time, via an Umbrella Company Are you ready to embark on an exciting journey to shape the future of AI? Our client is on the lookout for a talented AI Engineer to engineer enterprise-grade Generative AI agents. If you have a passion for innovation and a knack for problem-solving, this opportunity is for you! What We're Looking For: Previous experience supporting the creation of Agentic AI Agents Expertise in Generative AI and LLM selection. Strong background in decision support and conversational AI. Familiarity with engineering prompts and agent patterns. Knowledge of cloud standards and privacy governance. Experience in monitoring, quality evaluation, and bias mitigation. A commitment to explainability and auditability. Passion for integrating human-in-the-loop controls. What You'll Be Doing: As an AI Engineer, you will play a pivotal role in creating intelligent automation and conversational experiences by leveraging the power of large language models (LLMs) and orchestration frameworks. Your responsibilities will include: Designing Architecture: Define and own the architecture for enterprise-grade Generative AI and agent systems, ensuring alignment with cloud and organizational standards. Translating Business Needs: Convert business requirements into agent solutions, selecting the right agent patterns with clear success metrics and risk controls. Building GenAI Agents: Develop agents that seamlessly integrate LLMs with retrieval, tools, APIs, and structured reasoning for reliable and safe performance. Implementing RAG Solutions: Optimize Retrieval-Augmented Generation solutions, ensuring secure and permission-aware access to enterprise knowledge sources. Engineering Safety Measures: Create prompts and policies that enforce Responsible AI principles, focusing on bias mitigation, explainability, and human-in-the-loop controls. Ensuring Performance: Maintain the performance and resilience of GenAI systems through optimization and robust fallback strategies. Embedding Governance: Design with security, privacy, and governance in mind to support compliance and enterprise risk management. Integrating Agents: Collaborate with platform teams to build reusable components and deliver scalable, production-ready AI capabilities. Troubleshooting and Innovation: Act as a senior subject matter expert to resolve issues, lead investigations, and drive experimentation with emerging models and tools. Influencing Stakeholders: Engage with key stakeholders to articulate trade-offs and strategic decisions effectively. Why Join Us? This is a fantastic opportunity to work in a dynamic environment where your skills will be valued, and your contributions will make a real impact. You'll be part of a forward-thinking team that is committed to pushing the boundaries of AI technology! Ready to Make a Difference? If you're excited about this opportunity and believe you have the skills to excel, we want to hear from you! Apply today and take the next step in your career with us. Let's innovate together! We can't wait to meet you! We use generative AI tools to support our candidate screening process. This helps us ensure a fair, consistent, and efficient experience for all applicants. Rest assured, all final decisions are made by our hiring team, and your application will be reviewed with care and attention. Adecco is a disability-confident employer. It is important to us that we run an inclusive and accessible recruitment process to support candidates of all backgrounds and all abilities to apply. Adecco is committed to building a supportive environment for you to explore the next steps in your career. If you require reasonable adjustments at any stage, please let us know and we will be happy to support you.

Position: Forward Deployed Engineer (B2) Location: London, UK (Hybrid) Permanent position Job Requirements Experience building GenAI applications, including RAG, multi-agent systems, fine-tuning, etc., with tools such as LangChain, LangGraph etc. Clear understanding of Model Context Protocols, A2A Protocols, Agent Developeer Kit and working experience with LLMs Expertise in deploying production grade GenAI solutions, including evaluation and optimizations; Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog, Slack. Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike 5+ years of engineering and technical deployment experience in a customer-facing set up Should scoped and delivered complex systems in rapid and ambiguous environments Delivered production-grade code across frontend and backend using Python, JavaScript, or similar stacks Understand how AI model behaviour affects product experience Communicate clearly with engineers, product teams, and customer stakeholders Flag risks early and seek attention as per the severity Key responsibilities: Help clients integrate and adopt the offerings; demonstrate the impact / outcomes the offerings commited such as KPI improvements and help client succeed Embed within the client landscape, understand their domain and co-develop solutions with the core product engineering teams Own technical delivery across multiple deployments from prototype to stable release Build bespoke AI and transformative agentic AI solutions Technical debugging and root cause analysis Rapid prototyping Implement and administer best practices

Forward Deployed Engineer Generative AI / LLM Deployment GenAI LangChain RAG AWS Kubernetes Customer-Facing We are hiring a Forward Deployed Engineer to lead the deployment of production-grade Generative AI and LLM solutions into enterprise environments. This is a hands-on, customer-facing role focused on building and deploying RAG pipelines, multi-agent systems and fine-tuned LLM applications using tools such as LangChain and LangGraph. You will embed with client teams, own technical delivery from prototype to production, and demonstrate measurable KPI impact. Key Responsibilities Design and deploy GenAI / LLM applications (RAG, agentic AI, fine-tuning) Lead production deployment on AWS, Azure or GCP Build scalable backend systems in Python (JavaScript a plus) Manage infrastructure using Kubernetes, Docker, Terraform Own end-to-end technical delivery across multiple client deployments Conduct debugging, optimisation and root cause analysis Communicate complex AI concepts to technical and non-technical stakeholders Requirements Strong experience building and deploying LLM / Generative AI solutions Hands-on with LangChain, RAG, multi-agent systems Cloud ML deployment experience (AWS, Azure or GCP) DevOps tooling: Kubernetes, CI/CD, GitHub, GitOps Customer-facing technical delivery experience Background in Machine Learning, Data Science or AI Engineering This role suits a Senior Machine Learning Engineer, Applied AI Engineer, AI Solutions Engineer or LLM Engineer who enjoys client impact, rapid prototyping and owning delivery in fast-moving environments. Apply now to work at the forefront of enterprise AI deployment and agentic systems.

We're representing a multinational advanced entertainment electronics company working with the likes of Netflix, Disney, and PL football teams. The culture is techy. Profit-sharing, a good salary package and employee councils and working groups. They take care of their employees, and their engineers have clout. They're working on driving forwards automation, including implementing agentic workflows. They're looking for a Software Test Engineer to help drive forward software automation for their software-driven electronics. Responsibilities Perform end-to-end quality assurance testing of software releases, from development through to production. Investigate and reproduce reported faults, documenting findings clearly within the issue-tracking system. Create structured, comprehensive test plans and detailed test cases for both manual and automated testing. Design, develop and execute automation scripts to improve coverage and efficiency. Collaborate with product management, developers and project teams to clarify requirements and feature specifications. Contribute to improving QA methodologies, processes and overall testing effectiveness. Requirements Degree in a relevant engineering discipline with hands-on experience in software and embedded systems testing Proven ability to troubleshoot complex technical issues, manage bug tracking and prioritise effectively across teams. Strong communication skills, analytical mindset, attention to detail, and working knowledge of high-level languages (preferably Python). Desirable Interest or experience within live entertainment, lighting control or video processing environments. Familiarity with version control systems such as Git and packet analysis tools (e.g. Wireshark). Understanding of networking fundamentals and protocols including DMX-512, ArtNet and sACN. If you're naturally curious and like cool technology, apply now!

Join us on a transformative journey as a Solution Architect-Component Designer Assurance & AI, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unapparelled customer experiences. Operational Support Systems (OSS) & Tools is a newly formed functional unit in the Network Product domain at Barclays. The Barclays OSS & Tools Engineering team is responsible for the design, build and operate of the underlying OSS infrastructure and toolchain across cloud, data centre, campus and branch that are required to run the Barclays Global Network at scale. To be successful as a Solution Architect, you should have experience with Demonstrable experience of building high scale observability solutions using open-source tooling like ELK, Grafana, Prometheus, Nagios, Telegraf and others. Knowledge and demonstrable hands-on experience with middleware technologies (Kafka, API gateways and others) and Data Engineering tools/frameworks like Apache Spark, Airflow, Flink and Hadoop ecosystems. Understanding of network technology fundamentals, Data Structures, scalable system design and ability to translate information in a structured manner for wider product and engineering teams to translate into working solution. Some other highly valued skills may include Knowledge of DevOps tooling, GitOps, CI/CD, configuration management, Jenkins, build pipelines and source control systems. Working knowledge of cloud infrastructure services: compute, storage, networking, hybrid connectivity, monitoring/logging, security and IAM. Programming experience in one of the highlevel languages like Python, Java, Golang and NetDevOps automation and AI engineering (GenAI/Agentic AI), API service development. Proficiency in Agile Methodologies Scrum/Kanban, backlog and workflow mgmt. and SRE specific reporting (MTTR, deployment frequency, SLO and others) You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills Location is Knutsford Purpose of the role To design, develop, and implement solutions to complex business problems, collaborating with stakeholders to understand their needs and requirements, and design and implement solutions that meet those needs and create solutions that balance technology risks against business delivery, driving consistency. Accountabilities Design and development of solutions as products that can evolve, meeting business requirements that align with modern software engineering practices and automated delivery tooling. This includes identification and implementation of the technologies and platforms. Targeted design activities that apply an appropriate workload placement strategy and maximise the benefit of cloud capabilities such as elasticity, serverless, containerisation etc. Best practice designs incorporating security principles (such as defence in depth and reduction of blast radius) that meet the Bank's resiliency expectations. Solutions that appropriately balance risks and controls to deliver the agreed business and technology value. Adoption of standardised solutions where they fit. If no standard solutions fit, feed into their ongoing evolution where appropriate. Fault finding and performance issues support to operational support teams, leveraging available tooling. Solution design impact assessment in terms of risk, capacity and cost impact, inc. estimation of project change and ongoing run costs. Development of the requisite architecture inputs required to comply with the banks governance processes, including design artefacts required for architecture, privacy, security and records management governance processes. Vice President Expectations To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures If managing a team, they define jobs and responsibilities, planning for the department's future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L - Listen and be authentic, E - Energise and inspire, A - Align across the enterprise, D - Develop others OR for an individual contributor, they will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment. Manage and mitigate risks through assessment, in support of the control and governance agenda. Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does. Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business. Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies. Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions. Adopt and include the outcomes of extensive research in problem solving processes. Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship - our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset - to Empower, Challenge and Drive - the operating manual for how we behave.

Microsoft Power Platform / Agentic AI Engineer Location : Liverpool Street, London (2-3 days on-site required) Contract Length : 6 months Daily Rate: 650 inside umbrella Why Join Us? At our client's organisation, you will be at the forefront of technology, driving innovation in the Capital Markets and Corporate Banking sectors. This is your chance to work with cutting-edge tools and technologies, while collaborating with a team that values creativity and forward-thinking solutions. Role Overview As a Microsoft Power Platform & Agentic AI Engineer, you will spearhead the development of intelligent, enterprise-grade AI solutions using Microsoft's low-code ecosystem. Your main focus will be on creating Copilot Studio agents, Power Automate workflows, and Power Apps that integrate seamlessly with enterprise systems. Key Responsibilities Power Platform & Copilot Studio Development Design and build conversational agents using Microsoft Copilot Studio. Develop Power Automate flows triggered by AI agents or business events. Create engaging Power Apps frontends integrated with GenAI services and enterprise data. Build and manage custom connectors to internal APIs and third-party services. Agentic Workflow Orchestration Architect multi-step agent workflows using: - Semantic Kernel SDK (C# or Python) - Azure OpenAI (GPT-4, function calling, chat completion) - Planner and Kernel Memory APIs for reasoning and memory - RAG pipelines grounded in enterprise data via Azure AI Search Microsoft 365 & Graph API Integration Enable agents to access and reason over content in SharePoint, OneDrive, Teams, Outlook, and Planner. utilise Microsoft Graph API to retrieve and manipulate enterprise data efficiently. Enterprise Data & AI Services Integration Integrate with Azure AI Search, Azure Form Recognizer, and Azure Language Services for enhanced document understanding and summarization. Cloud Engineering & Security Deploy solutions using Azure Kubernetes Service (AKS) or Azure Container Apps. Ensure robust security with Azure Key Vault, Microsoft Entra ID, and best practises in identity and access control. What We're Looking For Technical Skills & Technologies: Strong experience with Power Platform, including Copilot Studio, Power Automate, Power Apps, and custom connectors. Proficiency in Microsoft Graph API, Azure OpenAI, and Semantic Kernel. Solid programming skills in Python and/or C#. Familiarity with LangChain, AutoGen, or similar orchestration frameworks. Experience with Azure AI Search, Form Recognizer, and Language Services. Knowledge of CI/CD, DevSecOps practises, and responsible AI frameworks. We are searching for someone with a proven track record of delivering agent-based or GenAI solutions in enterprise or regulated environments. Your enthusiasm and problem-solving mindset will be key to thriving in this role! Adecco is a disability-confident employer. It is important to us that we run an inclusive and accessible recruitment process to support candidates of all backgrounds and all abilities to apply. Adecco is committed to building a supportive environment for you to explore the next steps in your career. If you require reasonable adjustments at any stage, please let us know and we will be happy to support you.

Lead AI Engineer - ContractSR2 is proud to be supporting a flagship UK government AI programme, delivering a first-of-its-kind, citizen-facing solution at a national scale. This is an opportunity to step into the Lead AI Engineer role, taking ownership of the architecture and delivery of advanced agentic AI backends.What you'll do Lead the design and implementation of scalable agentic AI systems using modern frameworks. Architect and develop autonomous agents with planning, reasoning, and execution capabilities. Build and experiment with multi-agent systems that collaborate effectively. Develop agent memory systems and knowledge management tools. Evaluate, prototype, and select emerging AI technologies for experimental use cases. Apply open standards (e.g. MCP) to ensure interoperability across platforms. What we're looking for Proven experience in building agentic backends - able to describe the purpose of applications delivered, the tech stack/frameworks used, and your direct contributions. Strong Python development skills (5+ years), with solid software engineering foundations. Demonstrable track record in experimental AI research and applying emerging frameworks. Innovative problem-solver, comfortable leading technical direction in complex environments. Active SC clearance or eligibility to obtain. Why this role? This is a unique, long-term programme at the cutting edge of government AI, combining innovation, scale, and meaningful public impact. You'll be at the heart of shaping a system that could transform citizen-facing services across the UK.