11 of 11 Contract Retrieval-Augmented Generation Jobs in the UK excluding London

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 ...

Design, build, and deploy LLM-powered applications and GenAI solutions Develop and optimise prompt engineering strategies for performance and accuracy Implement RAG (Retrieval-Augmented Generation) pipelines using structured and unstructured data Fine-tune and customise foundation models and LLMs where required. Integrate GenAI solutions … software engineering, data science, or machine learning Proven experience building and deploying LLM/Generative AI applications in production environments Hands-on experience with RAG architectures, embeddings, and vector search Experience working with LLM APIs and frameworks (e.g., OpenAI, Azure OpenAI, Anthropic, Hugging Face) Strong understanding of prompt engineering techniques ...

outcomes. The Role and Deliverables Design, build, and maintain production-grade AI-enabled applications consuming standardised GenAI services such as LLM-based capabilities, RAG, summarisation, and classification. Develop cloud-native microservice or full-stack applications using API-led architectures. Integrate AI capabilities securely and reliably, in line with platform standards ...

Architect Professional* Databricks Certifications* CDMP Certification* Terraform, Bicep or Infrastructure-as-Code experience* dbt, Airflow or modern orchestration frameworks* Experience supporting AI, GenAI or RAG-based architectures* Experience within Financial Services, Healthcare, Life Sciences, Energy, Retail or Manufacturing Robert Half Ltd acts as an employment business for temporary positions ...

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/ ...

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 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 ...

proof-of-concept role. You will be responsible for delivering secure, resilient and scalable AI-enabled applications that consume standardised GenAI services, including LLMs, RAG, summarisation and extraction capabilities. You will work closely with GenAI Engineers, Platform Engineers, Product, Architecture and Business Delivery teams to turn business problems into robust … responsibilities: * Design, build and maintain AI-enabled applications using enterprise GenAI services* Develop production-grade microservices and/or full-stack applications* Integrate LLM, RAG, summarisation and extraction services into secure, scalable applications* Own end-to-end delivery, including development, CI/CD, deployment, monitoring and incident resolution* Build ...

for. What you'll be working on as an AI Engineer - LLM & Agentic Systems: Designing and building AI agents and agentic workflows - combining LLMs, RAG, reasoning, memory and tool orchestration to solve real, complex business problems. Owning delivery end-to-end - from initial exploration through to production deployment, integration … with clear, real-world examples you can speak to confidently. Hands-on experience building AI agents including tool use, orchestration and multi-step reasoning - RAG systems that actually deliver, not just proofs of concept. Strong Python skills and solid machine learning foundations - able to write clean, production-grade code with ...

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. Key Responsibilities Automated Adversarial Testing: Build and integrate automated red teaming suites into CI/… within FCA, DORA, or EU AI Act frameworks. AWS Bedrock Ecosystem: Hands-on experience configuring, testing, and bypassing Bedrock Guardrails, Agents, and Knowledge Bases (RAG) . AI Security & Fundamentals: Solid understanding of Foundation Models, tool use (function calling), OWASP LLM Top 10 , and NIST AI RMF . Automation Stack: Strong ...