126 to 150 of 304 Retrieval-Augmented Generation Jobs in the UK

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 ...

models (DAX and Power Query) Exposure to ML/AI concepts (e.g. scikit-learn, TensorFlow) or an interest in preparing data for LLMs, RAG architectures or predictive models Experience with Docker and/or Terraform (desirable) What You Will Learn & What Liquidline Can Offer You Being a part of Liquidline ...

production environments — not just prototypes. Key experience required: • Python and production-grade coding • LLMs, AI Agents & Agentic Workflows • LangChain/LangGraph or similar frameworks • RAG Systems • MCP/FastMCP/FastAPI architectures • Cloud platforms (AWS, Azure, or GCP) • AI system deployment, orchestration & optimisation. This role offers the opportunity to work ...

/ML frameworks (e.g. LangChain, OpenAI API, Hugging Face, TensorFlow, PyTorch) * Comfortable writing production-ready code - Python particularly valued * Understanding of LLMs, prompt engineering, RAG pipelines or similar AI architectures * Ability to communicate technical ideas clearly to non-technical stakeholders * A proactive mindset - someone who spots opportunities and takes initiative ...

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 ...

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 ...

prioritise AI opportunities across the organisation Required ExperienceEssential Deep expertise in Python and relevant AI/ML frameworks and SDKs Proven experience building RAG pipelines that operate effectively in production environments Hands-on experience with model packaging, deployment, and production AI workflows Strong understanding of enterprise infrastructure concepts including VNets ...

Familiarity with AI-assisted development tools such as GitHub Copilot, Claude, and Cursor. Azure AI Engineer certification or equivalent practical experience. Understanding of MCP, RAG architectures, or vector databases. Benefits Industry-leading training and development opportunities. Competitive salary with progression potential. 23-days holiday allowance, increasing with length of service ...

designing and optimising multi-agent systems for reliability and production performance Understanding of prompt engineering techniques including few-shot learning, chain-of-thought and RAG Familiarity with LLM evaluation strategies and how to measure whether your system is actually working Hands-on with AI orchestration frameworks: LangGraph, LangChain, DSPy ...

routing strategies , selecting between Claude, OpenAI, and open-source LLMs based on cost, latency, and use case. Architect and deliver RAG (Retrieval-Augmented Generation) solutions using vector databases. Define and enforce AI governance frameworks , including model risk management, security, and compliance. Lead model lifecycle … expertise with AWS Bedrock and multi-model AI architectures. Practical experience working with Claude, OpenAI APIs, and open-source LLMs . Deep understanding of RAG architectures , embeddings, and vector databases (eg Pinecone, Weaviate, OpenSearch, FAISS). Demonstrable experience defining and applying AI governance and responsible AI frameworks . Strong knowledge ...

Engineering community. What youll bring: A strong understanding of AI, machine learning and agent-based AI concepts, including Retrieval Augmented Generation (RAG), multi-agent systems and conversational agents. Experience developing AI solutions using programming languages such as Python, or similar languages used ...

platforms such as AWS, GCP, or Azure. What you’ll bring Deep, hands-on experience building and deploying production-grade AI systems using LLMs, RAG pipelines, MCPs, and agentic workflows Proven track record of leading complex, client-facing engagements with a forward-deployed mindset, partnering with both technical and business ...

tools, and cloud platforms such as AWS, GCP, or Azure. What you’ll bring: Proven hands-on experience building production-grade solutions using LLMs, RAG pipelines, MCPs, and agentic workflows A forward-deployed, client-first mindset, with experience working directly with both technical teams and business stakeholders Strong delivery capabilities ...

Role 2: Applied AI Engineer Strong backend engineering experience (Python preferred) Deep knowledge of CI/CD, Docker, Kubernetes, and Git workflows Experience building RAG pipelines and AI agent orchestration systems Minimum 5 years of experience 📩 Interested? Message me here or email mmatysik@trg-uk.com ...

fundamentals are there Solid Kubernetes experience (around 80% of the role), with some serverless on top Hands-on experience with LLM-based applications — RAG, vector databases, agent frameworks Product-minded and commercially aware — this isn't a pure SRE or ops profile Comfortable working across Data Science, Engineering, Product ...

architectural calls, mentored others, and influenced how a team builds, not just what it ships Strong hands-on AI/LLM skills: prompt engineering, RAG, model evaluation and agent frameworks. You know how these work in production, not just in demos Deep expertise in Node.js, with solid experience ...

with agents, tool calling or LLM orchestration. A background in lawtech/legaltech or other regulated domains. Programming in Python. Deeper experience with LLMs, RAG techniques and evaluation. Knowledge of Docker, containerisation and serverless technologies. AWS Certification is a plus. Education and Experience: Bachelor’s degree in Computer Science, Information ...

agentic AI architectures, with experience integrating AI securely and at scale Practical experience in enterprise AI governance, prompt engineering, and deployment approaches (including RAG, fine-tuning considerations, and risk mitigation) Experience leveraging AI-assisted development tools (e.g. GitHub Copilot, Claude Code) to materially improve engineering productivity and delivery outcomes ...

agentic AI architectures, with experience integrating AI securely and at scale Practical experience in enterprise AI governance, prompt engineering, and deployment approaches (including RAG, fine-tuning considerations, and risk mitigation) Experience leveraging AI-assisted development tools (e.g. GitHub Copilot, Claude Code) to materially improve engineering productivity and delivery outcomes ...

prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting … collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma ...

prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting … collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma ...

ensure alignment with architecture standards and pattern sArchitect AI-enabled solutions incorporating LLM-based assistants, multi-agent orchestration, Retrieval Augmented Generation (RAG), and vector searc hPerform rapid prototyping and technical feasibility assessments to prove the value of new propositions through MVPs and pilot sCollaborate ...

Azure AI, GenAI and Agents. Experience with digital assistant solutions enhanced by AI such as Microsoft Copilot. Demonstrable experience with Retrieval-Augmented Generation. Solid understanding of MLOps. Ability to engage confidently with clients and present technical solutions clearly. It would be great if you had: Experience ...

comfortable with backend architecture and API design Hands-on experience with LLMs and agent frameworks, in production or serious personal projects Solid understanding of RAG, vector stores, prompt engineering, and context management Experience with data pipelines and handling both structured and unstructured data CS, data, or software background, formal ...

they’re looking for: Strong experience with Python in a production environment Hands-on experience with LLMs or applied AI (prompt engineering, fine-tuning, RAG, etc.) Experience building APIs and backend services Solid understanding of cloud platforms Ability to work in a fast-paced, product-driven environment Why join? Work ...