151 to 175 of 277 Retrieval-Augmented Generation Jobs in the UK

optimising prompts to ensure consistent, high-quality LLM outputs. Building and deploying AI-powered workflows that connect LLMs with business applications, APIs, and automation tools. Implementing RAG (Retrieval-Augmented Generation) pipelines to integrate enterprise data. Rapidly prototyping and iterating on AI solutions to demonstrate business value. Advising on responsible AI practices, governance, and compliance. … frameworks. Proficiency in Python or JavaScript for prototyping and integration work. Experience using automation platforms (UiPath, Power Automate, Zapier, n8n) and APIs. Knowledge of vector databases and embeddings for RAG pipelines. Excellent communication skills and the ability to translate business needs into technical solutions. This is a fantastic opportunity for an engineer who loves solving problems with AI and wants More ❯

SINDy) Working knowledge of cell biology. Experience with Python, C, R or related scientific computing languages. Preferred Qualifications - Experience working with causal representation learning Experience with RAG (retrieval-augmented generation) and GraphRAG a big plus Experience with building and deploying software on GitHub, PyPI, Anaconda Cloud, and Docker Hub, as well as use of More ❯

AI capabilities at scale. Automating infrastructure/model deployments using Kubernetes, Terraform, and CI/CD pipelines. Building and managing vector databases and retrieval systems to support RAG pipelines. Working with LLM frameworks like LangChain , LangGraph , CrewAI , or similar tools. Partnering closely with engineering, security, and product teams to deliver safe, production-ready AI systems. What They're More ❯

public and private sector clients. Details- Proven experience building Agentic AI systems (e.g. autonomous agents, multi-agent orchestration, tool use, memory, planning) Strong hands-on skills in Python, LLMs, RAG, and LangChain or similar frameworks Deep understanding of GCP services: Vertex AI, BigQuery, Cloud Functions, Pub/Sub, etc. Experience with batch and real-time data pipelines Familiarity with AI More ❯

to public and private sector clients.Details- Proven experience building Agentic AI systems (e.g. autonomous agents, multi-agent orchestration, tool use, memory, planning) Strong hands-on skills in Python, LLMs, RAG, and LangChain or similar frameworks Deep understanding of GCP services: Vertex AI, BigQuery, Cloud Functions, Pub/Sub, etc. Experience with batch and real-time data pipelines Familiarity with AI More ❯

be necessary for meetings, but these will be fully funded. As a GenAI/Python Engineer , you’ll help design, build, and scale AI-powered applications using tools like RAG, intelligent agents, and LLMs. This hands-on, client-facing role blends technical depth with consulting impact. You will: Develop and scale GenAI solutions from POCs to production. Lead development across More ❯

categories AI You will have: Actively used AI in your workflows Deployed AI systems at scale Built real-world systems with LLMs Used agent frameworks, like LangGraph or LangChain, RAG pipelines It would be interesting if you have: Contributed to the AI/ML community (open-source, publications, talks) Experienced optimising AI models through fine-tuning, distillation, or human-in More ❯

categories AI You will have: Actively used AI in your workflows Deployed AI systems at scale Built real-world systems with LLMs Used agent frameworks, like LangGraph or LangChain, RAG pipelines It would be interesting if you have: Contributed to the AI/ML community (open-source, publications, talks) Experienced optimising AI models through fine-tuning, distillation, or human-in More ❯

team that’s pushing boundaries in autonomous AI What You’ll Need: A strong foundation in data science and machine learning Hands-on use of modern AI tools (LLMs, RAG, LangChain, co-pilots, agentic workflows) Curiosity and eagerness to learn in a fast-moving AI landscape Experience collaborating with stakeholders and translating business problems into technical solutions What You’ll More ❯

team that’s pushing boundaries in autonomous AI What You’ll Need: A strong foundation in data science and machine learning Hands-on use of modern AI tools (LLMs, RAG, LangChain, co-pilots, agentic workflows) Curiosity and eagerness to learn in a fast-moving AI landscape Experience collaborating with stakeholders and translating business problems into technical solutions What You’ll More ❯

JavaScript, C#) Proven experience building solutions with the Microsoft Power Platform Familiarity with Azure or AWS A strong interest in AI/LLMs. Practical experience with Dify, or building RAG applications is a major plus. More ❯

JavaScript, C#) Proven experience building solutions with the Microsoft Power Platform Familiarity with Azure or AWS A strong interest in AI/LLMs. Practical experience with Dify, or building RAG applications is a major plus. More ❯

a founder or founding engineer - you know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external stakeholders Our values Trust More ❯

Partnering with stakeholders to scope problems and identify the right solution - whether leveraging existing AI tools or building custom workflows & solutions. Designing and implementing agentic systems using techniques spanning RAG, grounding, prompt engineering, and orchestration on a GCP-first stack. Building and maintaining production ML pipelines and services for non-GenAI use cases (e.g. recommender systems, customer segmentation models, marketing … of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying and operating ML systems in production (batch and real-time). Familiarity with RAG architectures, prompt engineering, and evaluation techniques. Strong grasp of security, privacy, and governance principles (IAM, secrets, PII handling). Excellent communication skills and ability to work with non-technical stakeholders. More ❯

AI capabilities at scale. Automating infrastructure/model deployments using Kubernetes, Terraform, and CI/CD pipelines. Building and managing vector databases and retrieval systems to support RAG pipelines. Working with LLM frameworks like LangChain , LangGraph , CrewAI , or similar tools. Partnering closely with engineering, security, and product teams to deliver safe, production-ready AI systems. What They’re More ❯

AI capabilities at scale. Automating infrastructure/model deployments using Kubernetes, Terraform, and CI/CD pipelines. Building and managing vector databases and retrieval systems to support RAG pipelines. Working with LLM frameworks like LangChain , LangGraph , CrewAI , or similar tools. Partnering closely with engineering, security, and product teams to deliver safe, production-ready AI systems. What They’re More ❯

AI capabilities at scale. Automating infrastructure/model deployments using Kubernetes, Terraform, and CI/CD pipelines. Building and managing vector databases and retrieval systems to support RAG pipelines. Working with LLM frameworks like LangChain , LangGraph , CrewAI , or similar tools. Partnering closely with engineering, security, and product teams to deliver safe, production-ready AI systems. What They’re More ❯

and recommend relevant advancements Requirements : 2-5+ years experience in an AI-focused enterprise/start-up Strong Python skills Strong practical experience in LLM concepts (context engineering, RAG, tool calling, workflows, multi-agent systems, MCP) Hands-on experience with frameworks like LangChain, Llamaindex, etc., vector stores, LLM APIs (e.g. OpenAI API, Anthropic API), and building MCP servers/ More ❯

teams to align requirements for application development within a graph and semantic framework. Contribute to data modelling and architecture to support reporting, UI development, and AI-driven tools (LLMs, RAG queries, etc.). Work within an Agile delivery framework to drive business value and measurable impact. Develop and present business-impacting deliverables to senior stakeholders and executive leadership. Track adoption More ❯

Vision/NLP Strong Software Engineering skills (3 years+) Developed LLM architecture and deployed LLM applications Uptodate with current trends in AI Some experience with applying latest techniques like RAG architecture, GenAI, Parallel training etc The role is hybrid, with adhoc requirements to be on client premises (London) this could be between 1-3 days a week, so we would More ❯

Vision/NLP Strong Software Engineering skills (3 years+) Developed LLM architecture and deployed LLM applications Uptodate with current trends in AI Some experience with applying latest techniques like RAG architecture, GenAI, Parallel training etc The role is hybrid, with adhoc requirements to be on client premises (London) this could be between 1-3 days a week, so we would More ❯

Bring Must-haves Strong understanding of machine learning techniques — clustering, NLP, deep learning Hands-on experience with feature engineering, model evaluation and data exploration Knowledge of modern AI tooling (RAG, fine-tuning, LLMs, agentic frameworks) Ability to bridge technical and commercial conversations confidently A logical, creative problem-solver who can turn data into ROI Nice-to-haves Spark/PySpark More ❯

we deliver value to our users. Main Duties and Responsibilities Build robust ingestion pipelines for PDFs/Word/Excel/Audio/JSON and semi structured sources. Design RAG systems: chunking strategies, document schemas, metadata, hybrid/dense retrieval, re ranking, and grounding. Manage vector/keyword indexes (e.g., Azure AI Search, pgvector, Pinecone/Weaviate). … Vault, private networking. Add observability: tracing/telemetry (OpenTelemetry, LangSmith), metrics, logs, cost and token usage monitoring, alerts. Apply evaluation & QA: regression suites, offline eval sets/golden data, RAG evals (faithfulness, answer relevance, citation correctness), A/B tests, win rate testing. Ensure reliability: rate limit handling, retries/backoff, idempotency, circuit breakers, caching (e.g., Redis/semantic cache More ❯

agents that democratise access to powerful computational biology tools, enabling researchers worldwide to leverage cutting-edge models via intuitive chat interfaces. Who We Are: We are building next-generation generative models that learn the fundamentals of biology. Our team pursues ambitious scientific goals with curiosity and a deep commitment to research excellence. Team members have previously contributed to … and frameworks such as LangChain or LlamaIndex, or you’ve built custom agent frameworks from scratch. You understand intelligent information retrieval, with experience in RAG (Retrieval-Augmented Generation), vector databases, and embedding models for knowledge extraction. You can architect complex workflows using orchestration tools such as Airflow, Prefect, or Temporal, or by More ❯

agents that democratise access to powerful computational biology tools, enabling researchers worldwide to leverage cutting-edge models via intuitive chat interfaces. Who We Are: We are building next-generation generative models that learn the fundamentals of biology. Our team pursues ambitious scientific goals with curiosity and a deep commitment to research excellence. Team members have previously contributed to … and frameworks such as LangChain or LlamaIndex, or you’ve built custom agent frameworks from scratch. You understand intelligent information retrieval, with experience in RAG (Retrieval-Augmented Generation), vector databases, and embedding models for knowledge extraction. You can architect complex workflows using orchestration tools such as Airflow, Prefect, or Temporal, or by More ❯