176 to 200 of 240 Retrieval-Augmented Generation Jobs in England

is integral to their agentic AI solutions. Requirements: Previous experience leading, managing and growing teams of AI Researchers and Engineers Strong technical knowledge and experience around AI agents, LLMs, RAG systems, reinforcement learning, fine-tuning, etc Data Engineering and Infrastructure knowledge and experience Strong product mindset Experience working in a B2B SaaS start-up or scale-up would be advantageous More ❯

is integral to their agentic AI solutions. Requirements: Previous experience leading, managing and growing teams of AI Researchers and Engineers Strong technical knowledge and experience around AI agents, LLMs, RAG systems, reinforcement learning, fine-tuning, etc Data Engineering and Infrastructure knowledge and experience Strong product mindset Experience working in a B2B SaaS start-up or scale-up would be advantageous More ❯

goes beyond static models to deliver autonomous, measurable business impact. To accelerate this capability, we're hiring a Senior Generative AI Engineer to design, build, and deploy next-generation AI ecosystems for global enterprises. You'll … join a hybrid London team (two days a week on-site) with strong flexibility for remote work. Your Role Design, build, and deploy generative AI systems (LLMs, retrieval-augmented architectures, embedding pipelines, agents) from prototype to production. Lead the full ML lifecycle: data extraction, modelling, fine-tuning, training, inference, deployment, and monitoring. Collaborate with product, engineering … engineers and raise the overall technical bar of the team. You Bring 5+ years of ML/AI engineering experience, including 3+ years deploying generative AI (LLMs, fine-tuning, RAG) in production. Strong technical grounding in Python, TensorFlow/PyTorch, transformer architectures (GPT, Llama, Mistral), vector databases, and prompt engineering frameworks. Proven record of delivering measurable ROI from AI projects. More ❯

goes beyond static models to deliver autonomous, measurable business impact. To accelerate this capability, we're hiring a Senior Generative AI Engineer to design, build, and deploy next-generation AI ecosystems for global enterprises. You'll … join a hybrid London team (two days a week on-site) with strong flexibility for remote work. Your Role Design, build, and deploy generative AI systems (LLMs, retrieval-augmented architectures, embedding pipelines, agents) from prototype to production. Lead the full ML lifecycle: data extraction, modelling, fine-tuning, training, inference, deployment, and monitoring. Collaborate with product, engineering … engineers and raise the overall technical bar of the team. You Bring 5+ years of ML/AI engineering experience, including 3+ years deploying generative AI (LLMs, fine-tuning, RAG) in production. Strong technical grounding in Python, TensorFlow/PyTorch, transformer architectures (GPT, Llama, Mistral), vector databases, and prompt engineering frameworks. Proven record of delivering measurable ROI from AI projects. More ❯

over 175,000 new developers signing up to use MongoDB every month, it's no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications. We are looking for passionate technologists to join our Pre-Sales organization to ensure that our growth is grounded and guided by strong technical alignment with … communicating its business value to the relevant stakeholders Sales Partnership: Collaborate with the sales team to drive account success through account planning, opportunity prioritization/qualification and pipeline generation strategy, while taking ownership of the technical aspects (including but not limited to technical discovery, demos, proof of value, presentations, sizing and documentation) Demand Generation: Proactively generate … Enhance your skills with partner and complementary technologies such as Apache Kafka and Kubernetes Design Patterns and Methodologies: Embrace best practices in microservices, DevOps, cloud, and security Cutting Edge RAG and AI Architectures: Help customers on their generative AI journeys and working with industry leading partners in the space Sales Techniques and Soft Skills: Effective Communication: Master presentations, demonstrations, and More ❯

Lead AI Engineer/Consultant - Greenfield Outside IR35 £600 - £750pd flexible for the right person RAG experience a must. About the Company Market leading SaaS organisation building out their AI function. About the Role This project is a greenfield build out of AI capabilities. They are starting with RAG use cases as a low bar, but are targeting a rich … deliver an AI capability. Lead design, architecture, and delivery of advanced AI/ML and generative AI solutions, ensuring scalable, secure, and production-ready system. Expert in MCP and RAG patterns. Design and build robust data and ingestion pipelines, integrate vector databases, and RSG. Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow). Hands … complex, data-rich environments. Skilled in setting team engineering practices: Git, CI/CD, automated testing for ML code, code reviews, and documentation. Preferred Skills Expert in MCP and RAG patterns . Experience in developing agentic AI systems Lead tech enablement and mentor engineers, fostering culture of reliability, continuous improvement, and collaboration. Excellent communication skills, able to translate technical strategy More ❯

Lead AI Engineer/Consultant - Greenfield Outside IR35 £600 - £750pd flexible for the right person RAG experience a must. About the Company Market leading SaaS organisation building out their AI function. About the Role This project is a greenfield build out of AI capabilities. They are starting with RAG use cases as a low bar, but are targeting a rich … deliver an AI capability. Lead design, architecture, and delivery of advanced AI/ML and generative AI solutions, ensuring scalable, secure, and production-ready system. Expert in MCP and RAG patterns. Design and build robust data and ingestion pipelines, integrate vector databases, and RSG. Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow). Hands … complex, data-rich environments. Skilled in setting team engineering practices: Git, CI/CD, automated testing for ML code, code reviews, and documentation. Preferred Skills Expert in MCP and RAG patterns . Experience in developing agentic AI systems Lead tech enablement and mentor engineers, fostering culture of reliability, continuous improvement, and collaboration. Excellent communication skills, able to translate technical strategy More ❯

of AI within 18 months. You'll be at the heart of innovation, working with the latest AI technologies, frameworks, and tools including Python, PyTorch, TensorFlow, Hugging Face, and RAG-based solutions. You'll make a real impact, collaborating with experienced technologists and finance professionals to deliver high-value AI solutions. Required Experience & Skills: 2+ years software development … z2bz0 years in AI/ML development. Python (mandatory), Java or TypeScript (advantageous) ML fundamentals, LLM integration, prompt engineering, RAG workflows, AI frameworks and Fine-tuning. Mindset: Self-motivated, growth-oriented, passionate about emerging AI tools. Environment: Comfortable in a Windows/Microsoft environment, with strong communication and stakeholder management skills. Location: Must be office-based in Finsbury Square, London … ownership of AI initiatives and work on impactful projects, apply now to join a high-growth, forward-thinking team in London. Keywords: AI Developer, Python Developer, Machine Learning, LLM, RAG, Prompt Engineering, AI Tools, PyTorch, TensorFlow, Hugging Face, Fintech Jobs London, Trading Platform, Lead AI, AI Engineer, AI Automation, AI Careers, AI London Jobs More ❯

AI capabilities at scale. We’re hiring an experienced, hands-on Machine Learning Engineer to architect and deliver production-grade AI system — with a strong focus on MCP, RAG, and real-world deployment . This project is a green field build out of AI capabilities. Whoever joins has an opportunity to work on the foundational architectural definition and implementation. … the Director of Engineering Architect, build and ship advanced AI/ML & Generative AI solutions — scalable, secure, production-ready Design data ingestion pipelines, integrate vector databases and retrieval-augmented systems Ship models via APIs, containers, or cloud-native services Own engineering excellence — Git, CI/CD, automated ML testing, IaC Influence technical direction and mentor other … translate AI strategy into measurable business outcomes What you bring Expert Python — LangChain, Semantic Kernel, PyTorch, TensorFlow Hands-on cloud delivery — Azure/AWS, Terraform, ECS Proven experience building RAG/MCP architectures 5+ years in applied ML or AI engineering roles Send us your profile now for immediate consideration. November start. More ❯

AI capabilities at scale. We’re hiring an experienced, hands-on Machine Learning Engineer to architect and deliver production-grade AI system — with a strong focus on MCP, RAG, and real-world deployment . This project is a green field build out of AI capabilities. Whoever joins has an opportunity to work on the foundational architectural definition and implementation. … the Director of Engineering Architect, build and ship advanced AI/ML & Generative AI solutions — scalable, secure, production-ready Design data ingestion pipelines, integrate vector databases and retrieval-augmented systems Ship models via APIs, containers, or cloud-native services Own engineering excellence — Git, CI/CD, automated ML testing, IaC Influence technical direction and mentor other … translate AI strategy into measurable business outcomes What you bring Expert Python — LangChain, Semantic Kernel, PyTorch, TensorFlow Hands-on cloud delivery — Azure/AWS, Terraform, ECS Proven experience building RAG/MCP architectures 5+ years in applied ML or AI engineering roles Send us your profile now for immediate consideration. November start. More ❯

Full Stack AI Software Engineer - Full Remote UK - £90,000 + Equity This role requires a software engineer with experience in implementing RAG pipelines and Vector Search (and hybrid AI searches, preferably). The client I am working with is an AI focused start-up backed by a £1.7M pre-seed investment. They are on a mission to streamline the … an early stage. What you'll work on: Backend APIs (Python/FastAPI): Build and maintain secure, high-performance services that drive AI features and data access at scale. RAG & vector search: Design and improve retrieval pipelines (embeddings, chunking, hybrid search, ranking, feedback loops), owning schema design, latency, and relevance across vector databases. LLM integration: Connect and orchestrate … AI development. Requirements: A motivated, hands-on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years’ experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient More ❯

DevOps Working closely with platform leads, architects, and SRE teams to ensure stable, scalable operations Supporting benchmarking, evaluation, and experiment tracking to measure LLM performance and cost Contributing to RAG implementations and vector-driven retrieval patterns Helping shape platform patterns, reusable components, and clear documentation Troubleshooting performance issues across distributed systems and cloud services What You’ll Bring … S3, SQS, DynamoDB, Bedrock RESTful API development with FastAPI, microservices, Terraform, GitOps workflows Prompt evaluation tools such as Promptfoo SQL and NoSQL experience: MySQL, PostgreSQL, MongoDB, Cassandra Exposure to RAG patterns and vector search technologies What Success Looks Like: Secure, reusable GenAI components running smoothly in production Faster engineering delivery through automation and DevOps maturity High observability and strong evaluation More ❯

DevOps Working closely with platform leads, architects, and SRE teams to ensure stable, scalable operations Supporting benchmarking, evaluation, and experiment tracking to measure LLM performance and cost Contributing to RAG implementations and vector-driven retrieval patterns Helping shape platform patterns, reusable components, and clear documentation Troubleshooting performance issues across distributed systems and cloud services What You’ll Bring … S3, SQS, DynamoDB, Bedrock RESTful API development with FastAPI, microservices, Terraform, GitOps workflows Prompt evaluation tools such as Promptfoo SQL and NoSQL experience: MySQL, PostgreSQL, MongoDB, Cassandra Exposure to RAG patterns and vector search technologies What Success Looks Like: Secure, reusable GenAI components running smoothly in production Faster engineering delivery through automation and DevOps maturity High observability and strong evaluation More ❯

DevOps Working closely with platform leads, architects, and SRE teams to ensure stable, scalable operations Supporting benchmarking, evaluation, and experiment tracking to measure LLM performance and cost Contributing to RAG implementations and vector-driven retrieval patterns Helping shape platform patterns, reusable components, and clear documentation Troubleshooting performance issues across distributed systems and cloud services What You’ll Bring … S3, SQS, DynamoDB, Bedrock RESTful API development with FastAPI, microservices, Terraform, GitOps workflows Prompt evaluation tools such as Promptfoo SQL and NoSQL experience: MySQL, PostgreSQL, MongoDB, Cassandra Exposure to RAG patterns and vector search technologies What Success Looks Like: Secure, reusable GenAI components running smoothly in production Faster engineering delivery through automation and DevOps maturity High observability and strong evaluation More ❯

DevOps Working closely with platform leads, architects, and SRE teams to ensure stable, scalable operations Supporting benchmarking, evaluation, and experiment tracking to measure LLM performance and cost Contributing to RAG implementations and vector-driven retrieval patterns Helping shape platform patterns, reusable components, and clear documentation Troubleshooting performance issues across distributed systems and cloud services What You’ll Bring … S3, SQS, DynamoDB, Bedrock RESTful API development with FastAPI, microservices, Terraform, GitOps workflows Prompt evaluation tools such as Promptfoo SQL and NoSQL experience: MySQL, PostgreSQL, MongoDB, Cassandra Exposure to RAG patterns and vector search technologies What Success Looks Like: Secure, reusable GenAI components running smoothly in production Faster engineering delivery through automation and DevOps maturity High observability and strong evaluation More ❯

researchers, engineers, and portfolio specialists, solving complex real-world problems. Competitive compensation with a performance-linked bonus. What You’ll Do Take ownership of designing and building next-generation AI systems that make complex financial data instantly accessible and actionable. Partner closely with data scientists, ML researchers, and frontend engineers to turn research concepts into robust, scalable production … deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases into production workflows is a major plus. A strong communicator who can translate technical complexity into business value and thrives in collaborative, cross-functional environments. Passion More ❯

researchers, engineers, and portfolio specialists, solving complex real-world problems. Competitive compensation with a performance-linked bonus. What You’ll Do Take ownership of designing and building next-generation AI systems that make complex financial data instantly accessible and actionable. Partner closely with data scientists, ML researchers, and frontend engineers to turn research concepts into robust, scalable production … deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases into production workflows is a major plus. A strong communicator who can translate technical complexity into business value and thrives in collaborative, cross-functional environments. Passion More ❯

directly on several key product enhancements. You’ll work with Python/Django, Javascript and AWS. Our platform is also increasingly AI-powered, so familiarity with implementing AI solutions (RAG etc) is an advantage. You’ll be working on a project where everything is hosted in AWS and we have a lightweight automated deployment process. You’ll work alongside a …/or ReactJS. Working understanding of data capture and performance tracking, a willingness to contribute to design and UX decisions. AI familiarity with working on Gen AI projects, including RAG and API integration. Ability to work within project timelines, proactively communicate any delays and contribute to task re-prioritisation to keep things on track Experience in developing websites, web applications More ❯

directly on several key product enhancements. You’ll work with Python/Django, Javascript and AWS. Our platform is also increasingly AI-powered, so familiarity with implementing AI solutions (RAG etc) is an advantage. You’ll be working on a project where everything is hosted in AWS and we have a lightweight automated deployment process. You’ll work alongside a …/or ReactJS. Working understanding of data capture and performance tracking, a willingness to contribute to design and UX decisions. AI familiarity with working on Gen AI projects, including RAG and API integration. Ability to work within project timelines, proactively communicate any delays and contribute to task re-prioritisation to keep things on track Experience in developing websites, web applications More ❯

feedback loops. 25% Architect & scale Own reliability, latency, and cost. Design online/offline eval harnesses, canaries, and SLAs; operate GPUs/accelerators where needed. Stand up and harden RAG pipelines (indexing, retrieval policies, grounding, guardrails) and agent frameworks. Take basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost … building production ML/back‐end systems; 2+ years leading while coding. Expert Python ; strong back‐end chops (e.g., FastAPI, gRPC, Postgres, pub/sub/streams). Agents & RAG: Fluency with at least one agent framework ( ADK preferred ). Proven track record shipping AI agents and building RAG pipelines. LLM + DS depth: Prompting/tooling, retrieval More ❯

feedback loops. 25% Architect & scale Own reliability, latency, and cost. Design online/offline eval harnesses, canaries, and SLAs; operate GPUs/accelerators where needed. Stand up and harden RAG pipelines (indexing, retrieval policies, grounding, guardrails) and agent frameworks. Take basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost … building production ML/back‐end systems; 2+ years leading while coding. Expert Python ; strong back‐end chops (e.g., FastAPI, gRPC, Postgres, pub/sub/streams). Agents & RAG: Fluency with at least one agent framework ( ADK preferred ). Proven track record shipping AI agents and building RAG pipelines. LLM + DS depth: Prompting/tooling, retrieval More ❯

Senior AI Engineer Python, PyTorch, LLMs, RAG, Knowledge Graphs I’m working with one of the most ambitious AI startups in London, and they’re quickly becoming one of the leaders in the intersection of Generative AI and Finance💸 The vision? Replace clunky PDFs, fragmented data, and manual analysis with multi-agent AI systems that read, reason, and cite financial … insights. Why this role stands out: 🤖 Work directly on multi-agent LLM systems powering deep financial research 🧠 Tackle complex AI problems like knowledge graphs, RAG pipelines, citations, and personalisation 🚀 Join a tight-knit 3-person AI team at a company 8 months ahead of roadmap What they’re looking for: 3–6 years’ experience writing production-grade code Strong foundation … in machine learning (PyTorch/JAX/TensorFlow) Deep understanding of LLMs and RAG, not just LangChain wrappers Bonus: Research internships, papers, or early-stage AI product builds Someone who wants to build real things, not just publish Other details: 💸 Up to £140k + strong equity 📍2–3 days/week in the London office 📅 Process can wrap in under More ❯

Senior AI Engineer Python, PyTorch, LLMs, RAG, Knowledge Graphs I’m working with one of the most ambitious AI startups in London, and they’re quickly becoming one of the leaders in the intersection of Generative AI and Finance💸 The vision? Replace clunky PDFs, fragmented data, and manual analysis with multi-agent AI systems that read, reason, and cite financial … insights. Why this role stands out: 🤖 Work directly on multi-agent LLM systems powering deep financial research 🧠 Tackle complex AI problems like knowledge graphs, RAG pipelines, citations, and personalisation 🚀 Join a tight-knit 3-person AI team at a company 8 months ahead of roadmap What they’re looking for: 3–6 years’ experience writing production-grade code Strong foundation … in machine learning (PyTorch/JAX/TensorFlow) Deep understanding of LLMs and RAG, not just LangChain wrappers Bonus: Research internships, papers, or early-stage AI product builds Someone who wants to build real things, not just publish Other details: 💸 Up to £140k + strong equity 📍2–3 days/week in the London office 📅 Process can wrap in under More ❯

Implement testing and evaluation frameworks for LLM applications, covering prompt testing, output quality metrics and agent behaviour validation. ● Apply relevant AI technologies as needed, including retrieval systems (RAG, GraphRAG), knowledge graphs, vector databases or data pipelines. Role Requirements Work Experience ● At least five years as a software engineer on commercial platforms, with demonstrable experience building production LLM-powered … Model Context Protocol (MCP) or Agent-to-Agent (A2A). ● LLM evaluation tooling (OpenAI Evals, LangSmith, custom evaluation harnesses). ● Advanced agent patterns: multi-agent systems, supervision, delegation strategies. ● RAG, GraphRAG and knowledge graph design and implementation. ● Vector databases and similarity search systems. ● Graph databases (ArangoDB, Neo4j, Neptune) and property graph modelling. ● Data engineering: ETL pipelines, document processing, schema design More ❯

The role The role is building AI applications based on LLM and models such as GPT and BERT You'll make use of Python programming, Pyspark, tensorflow, HuggingFace, LangChain, RAG techniques, interfacing with diverse data sets. Cloud data platforms and a diverse set of tools for AI app deployment. The opportunity Work at the forefront of the industry. It's … on experience in a commercial environment, working on AI/ML applications Multi cloud exposure (Azure/AWS/GCP) . Some of the following - Pytorch, GPT/BERT, RAG, Apache Airflow, Power Automate, Azure logic apps, RPA/Zapier, HuggingFace, LangChain... Background in Data Science or Software Engineering The values and ethos of this business Innovation with real purpose More ❯