1 to 25 of 33 Contract Retrieval-Augmented Generation Jobs in England

Data/RAG Engineer - watsonx.ai & Data Contract | July-December 2026 Up to £550 per day | Inside IR35 UK-based | Mostly Remote (occasional onsite required) British-born nationals or UK residents (5+ years) | One passport only Previous SC clearance highly advantageous Build AI-driven solutions using watsonx We're looking … experienced Data/RAG Engineer to support the delivery of a high-profile AI MVP using watsonx.ai and watsonx.data . This role will play a key part in designing, implementing and optimising Retrieval-Augmented Generation (RAG) pipelines and data foundations that enable LLM-driven ...

developing scalable Python-based applications within enterprise environments Building and optimising AI-driven solutions, including Retrieval-Augmented Generation (RAG) capabilities Working with graph databases and integrating complex data relationships into AI workflows Containerising applications and deploying services into Kubernetes environments Improving system performance, reliability … within large-scale organisations Hands-on AI engineering expertise, ideally within production environments Experience with Retrieval-Augmented Generation (RAG) and Microsoft Graph Retrieval Strong understanding of Kubernetes, containerisation, and deployment practices Experience building and maintaining CI/CD pipelines Knowledge of graph ...

that automatically generate structured player summary reports from statistical profiles or unstructured scouting notes Build retrieval-augmented generation (RAG) pipelines over internal scouting databases, enabling natural-language queries against recruitment records Automate repetitive analytical tasks so the recruitment team receives live, structured outputs ...

hands-on with Python and Azure , possessing a proven track record of designing and deploying Retrieval-Augmented Generation (RAG) patterns. Key Responsibilities Architect & Govern: Design and implement robust on-premises, cloud, and hybrid AI solutions, ensuring strict technical governance and best practices across … client relationships to secure consensus on complex technical architectures. Essential Skills Clearance: Active UK Government Security Check (SC). GenAI: Expertise in LLMs and RAG architectures. Python: Strong proficiency alongside PySpark for data engineering. Azure: Deep familiarity with native tools (AI Search, Document Intelligence). MLOps: Understanding of LLMOps frameworks ...

hands-on with Python and Azure , possessing a proven track record of designing and deploying Retrieval-Augmented Generation (RAG) patterns. Key Responsibilities Architect & Govern: Design and implement robust on-premises, cloud, and hybrid AI solutions, ensuring strict technical governance and best practices across … client relationships to secure consensus on complex technical architectures. Essential Skills Clearance: Active UK Government Security Check (SC). GenAI: Expertise in LLMs and RAG architectures. Python: Strong proficiency alongside PySpark for data engineering. Azure: Deep familiarity with native tools (AI Search, Document Intelligence). MLOps: Understanding of LLMOps frameworks ...

data scientists, software engineers, and business stakeholders. LLM & Agent Development: Build autonomous AI agents, implement Retrieval-Augmented Generation (RAG) pipelines, and fine-tune LLMs using PEFT techniques like LoRA. Data Engineering: Design and maintain robust ETL/ELT pipelines to process structured and unstructured ...

Responsibilities Design & Deliver: Architect and implement cloud and AI-ready solutions on Azure, building repeatable patterns and integration services that support next-generation workloads. Secure AI Architecture: Develop and scale secure infrastructure architectures that allow applications to safely access both cloud-based backend services and on-premises data … Beyond the Basics): Real-world enterprise experience designing and deploying solutions centred around agentic workflows, Retrieval-Augmented Generation (RAG), and vectorisation patterns, rather than purely self-taught or personal interest projects. Software Engineering & Tech Stack: High proficiency in Python and PowerShell for building automation ...

connectors and integrations across Microsoft 365, Power Platform, Dynamics, Azure, and third-party APIs. Implement retrieval-augmented generation (RAG) patterns, including knowledge libraries, data sources, grounding, and prompts. Optimize agent behavior through prompt engineering and iterative tuning. Collaborate with business teams to identify automation … building copilot agents Hands-on experience with Microsoft Copilot Studio, Power Platform, or other conversational AI frameworks. Strong understanding of LLMs, prompts, grounding, and RAG workflows. Proficiency with Power Automate, APIs, JSON, Microsoft Graph, and workflow automation. Experience working with Microsoft 365 services (SharePoint, Outlook, Teams, OneDrive). Ability ...

Agentic System Design: Build intelligent AI agents capable of autonomous task execution using LLMs and advanced reasoning frameworks. LLM Specialization: Implement RAG (Retrieval-Augmented Generation) pipelines and fine-tune models using PEFT/LoRA to create domain-specific insurance experts. Production Engineering: Design ...

Agentic System Design: Build intelligent AI agents capable of autonomous task execution using LLMs and advanced reasoning frameworks. LLM Specialization: Implement RAG (Retrieval-Augmented Generation) pipelines and fine-tune models using PEFT/LoRA to create domain-specific insurance experts. Production Engineering: Design ...

Agentic System Design: Build intelligent AI agents capable of autonomous task execution using LLMs and advanced reasoning frameworks. LLM Specialization: Implement RAG (Retrieval-Augmented Generation) pipelines and fine-tune models using PEFT/LoRA to create domain-specific insurance experts. Production Engineering: Design ...

levels. What you'll bring: Proven experience (3 years) in AI solution engineering, with a focus on large language models, prompt engineering, and RAG implementations. Strong skills in data analytics, MLOps practices, and API development. Knowledge of governance frameworks for AI/ML models. Python expertise for automation. Experience working ...

premises, cloud, and hybrid AI solutions. GenAI Leadership: Deploy and customize a variety of generative models, leveraging Azure OpenAI, Vector Databases, and RAG patterns. Technical Governance: Managed and governed technical teams to ensure best practices in AI data engineering. Stakeholder Management: Act as the primary technical point of contact, gaining ...

premises, cloud, and hybrid AI solutions. GenAI Leadership: Deploy and customize a variety of generative models, leveraging Azure OpenAI, Vector Databases, and RAG patterns. Technical Governance: Managed and governed technical teams to ensure best practices in AI data engineering. Stakeholder Management: Act as the primary technical point of contact, gaining ...

deployment and monitoring. Lead end to end delivery of AI and LLM based solutions across underwriting and insurance journeys Build and deploy agentic workflows, RAG pipelines, and LLM powered applications for internal and customer facing products Work across structured and unstructured data, collaborating closely with Machine Learning and GenAI specialists ...

Requirements AWS Bedrock Expert: Hands-on experience with Bedrock Agents, Knowledge Bases, and model lifecycle management. AI/ML Depth: Strong grasp of FMs, RAG, tool-use, and the failure modes of agentic workflows. Security & Compliance: Deep knowledge of NIST AI RMF, OWASP LLM Top 10, and UK/ ...

Requirements AWS Bedrock Expert: Hands-on experience with Bedrock Agents, Knowledge Bases, and model lifecycle management. AI/ML Depth: Strong grasp of FMs, RAG, tool-use, and the failure modes of agentic workflows. Security & Compliance: Deep knowledge of NIST AI RMF, OWASP LLM Top 10, and UK/ ...

Requirements AWS Bedrock Expert: Hands-on experience with Bedrock Agents, Knowledge Bases, and model lifecycle management. AI/ML Depth: Strong grasp of FMs, RAG, tool-use, and the failure modes of agentic workflows. Security & Compliance: Deep knowledge of NIST AI RMF, OWASP LLM Top 10, and UK/ ...

Requirements AWS Bedrock Expert: Hands-on experience with Bedrock Agents, Knowledge Bases, and model lifecycle management. AI/ML Depth: Strong grasp of FMs, RAG, tool-use, and the failure modes of agentic workflows. Security & Compliance: Deep knowledge of NIST AI RMF, OWASP LLM Top 10, and UK/ ...

Skills & Experience: Active SC Clearance (mandatory) Prior experience on Ministry of Defence (MOD) projects Python Applied Machine Learning and LLM integration RAG (Retrieval-Augmented Generation) systems LangChain or LangGraph To Apply: Submit a CV and confirmation of active SC clearance status. ...

. AWS Bedrock Stack: Hands-on experience with Agents, Knowledge Bases, Guardrails, and model lifecycles. AI/ML Core: Mastery of FMs, RAG, tool-use, and non-deterministic agent logic. Security Frameworks: Proficiency in OWASP LLM Top 10 and NIST AI RMF . Role 1: Identity Expert Mission: Secure ...

application Development: LLM fine-tuning adapting pretrained LLMs for specific tasks using techniques likeparameterefficient fine-tuning (PEFT) (e.g., LoRA, QLoRA). Implementing Retrieval-Augmented Generationpipelines to enhance the knowledge and accuracy of LLMs. Utilizing vector databases for efficient storage andretrieval of embeddings generated by LLMs. rafting ...

enterprise-wide AI platform adoption Essential Skills and Experience Strong Python development experience, particularly for automation and test frameworks Experience with LLM and RAG evaluation tooling, frameworks, or custom evaluation pipelines Expertise in automated testing across unit, integration, and regression testing environments Good understanding of agentic AI systems, associated risks ...

enterprise Agentic AI platforms. You will move beyond traditional software QA to build continuous safety pipelines, ensuring our non-deterministic LLM agents, RAG systems, and tool integrations are secure, resilient, and compliant before production release click apply for full job details ...

based workflows, integrating AI platforms, and delivering scalable cloud-native solutions. Responsibilities AI Agent Engineering Design and implement AI agents, including: Retrieval (RAG) Orchestration workflows Tool/function invocation Policy-based routing Build evaluation frameworks for accuracy, latency, and reliability Implement observability and monitoring for agent lifecycle … engineering experience Strong experience with cloud-native systems (APIs, microservices, containers, serverless) Experience building and deploying AI/LLM-based systems in production (agents, RAG, orchestration) Proficiency in Python, Java, or similar backend languages Experience with: CI/CD pipelines Infrastructure as code Monitoring and observability tools Hands-on experience ...