126 to 150 of 154 Retrieval-Augmented Generation Jobs in England

work to the wider development team. Demonstrable knowledge and experience in data mining, machine learning (including deep learning), generative AI (e.g., with Retrieval-Augmented Generation), and reinforcement learning. Software Development & Delivery Design, develop, test and maintain software applications using Java (8+), XSLT, XML, JSON ...

delivery of scalable, resilient AI/ML pipelines aligned to business goals. Build and deploy advanced ML, DL, and LLM solutions, including RAG, agentic architectures, and evaluation frameworks. Mentor engineers in ML engineering, orchestration, and modern AI best practices. Communicate system behaviours, risks, and outcomes to both technical … Partner with the Head of AI Labs to turn AI research and strategy into production‐ready solutions. Key Requirements: Proven experience designing and productionising RAG pipelines and agentic AI architectures Hands‐on delivery of agent‐based AI systems with orchestration tools (e.g., LangChain, CrewAI) in production. Strong Python engineering skills ...

environment where experimentation, iteration, and innovation are actively encouraged. What You’ll Be Doing Designing and building production-grade AI systems using LLMs Developing RAG pipelines, vector search solutions, and agent-based workflows Creating robust evaluation frameworks to measure accuracy, reliability, and performance Building scalable APIs, services, and data pipelines … What We’re Looking For Experience building applications using LLM APIs, with a strong understanding of their strengths and limitations Hands-on experience with RAG architectures, vector databases, and prompt engineering Experience developing multi-step workflows or agentic systems (frameworks or custom builds) Strong programming skills (Python or similar), with ...

Agentic Engineer (MedTech) We’re partnering with an innovative MedTech company in North of England that is building next-generation intelligent healthcare solutions. They are now looking for an number of AI Agentic Engineer to help design, build, and deploy autonomous AI systems that will directly support clinical … experience include: Strong Python development experience Hands-on experience with LLMs and agent frameworks (e.g. LangChain, LlamaIndex, AutoGen or similar) Understanding of prompt engineering, RAG pipelines, and tool-using AI systems Experience working with APIs, data pipelines, and cloud platforms (AWS, Azure or GCP) Strong software engineering fundamentals (testing, version ...

Agentic Engineer (MedTech) Were partnering with an innovative MedTech company in North of England that is building next-generation intelligent healthcare solutions. They are now looking for an number of AI Agentic Engineer to help design, build, and deploy autonomous AI systems that will directly support clinical … experience include: Strong Python development experience Hands-on experience with LLMs and agent frameworks (e.g. LangChain, LlamaIndex, AutoGen or similar) Understanding of prompt engineering, RAG pipelines, and tool-using AI systems Experience working with APIs, data pipelines, and cloud platforms (AWS, Azure or GCP) Strong software engineering fundamentals (testing, version ...

lasting around nine months, building AI applications that solve real operational problems. Key Responsibilities • Design and implement LLM-powered applications for enterprise clients • Build RAG pipelines and AI workflows integrating enterprise data • Develop production APIs and backend services in Python • Implement evaluation frameworks and monitoring for AI systems • Optimise … squads Key Details • Salary: £75,000 – £90,000 • Working model: Hybrid (2–3 days per week in Central London) • Tech stack: Python, LLM APIs, RAG architectures, vector databases, agent frameworks, cloud platforms (AWS/GCP/Azure) • Visa sponsorship: Not available Interested? Please apply below. ...

Technical Skills Required Proven experience of: Agent Orchestration: LangChain, LangGraph, CrewAI - not just conceptual Agentic Coding Tools: Claude Code CLI, Cursor, OpenAI Codex, Copilot RAG & Vector Stores: Chroma, Weaviate, Pinecone, know where RAG breaks LLM APIs & SDKs: Anthropic, OpenAI, Gemini - prompt design, tool use Python/TypeScript: Primary languages … agent orchestration with memory, tool routing, and state management Built projects where AI (Claude Code, Codex, Cursor) wrote significant portions of the code Implemented RAG pipelines end-to-end - chunking, embedding, retrieval, re-ranking, evaluation Integrated agents with real enterprise APIs - not just OpenAI playground or sample data ...

intent accounts, generate tailored content, and execute strategic plays. They are building AI-first features to make this seamless and intelligent, from content generation to account strategy recommendations. The Role My client is seeking a senior Applied AI Engineer to lead the development and deployment of novel applications … Prototype and ship AI-powered product capabilities across the platform — from content generation to account intelligence and campaign automation. Design and implement RAG pipelines using vector databases like Qdrant or Weaviate for contextual awareness and retrieval. Build robust backend services in TypeScript to serve AI-driven features, including ...

semantic search and information retrieval. Knowledge of effective text chunking techniques for optimal processing and indexing of large documents or datasets. Expertise with RAG concepts and fundamentals (vectorDBs, semanticsearch, re‐rankers etc.), Expertise in implementing RAG systems that combine knowledge bases. Experience with multi‐agent frameworks/systems ...

deployment. Build MVPs and collaborate closely with Engineering and Product teams to bring ideas to life. Apply advanced machine learning and LLM techniques, including RAG, agents and NLP, where they drive meaningful customer and product impact. Work with large-scale datasets in cloud environments to deliver robust, scalable systems. Contribute … end. Proficiency in Python and SQL, with experience working on cloud-scale datasets. Practical experience with LLMs and applied AI, such as RAG, agents, or NLP. Experience building customer-facing or product-centric ML systems. A product-focused mindset, balancing experimentation with real-world value. Useful additional experience includes ...

/B experiments and performance dashboards. • Integrate AI agent functionality with applications through MCP servers and reliable tool configurations. • Develop secure and scalable RAG pipelines, including ingestion, text processing, metadata handling and vector search in GCP. • Embed security, compliance, GDPR controls and best‐practice engineering with clear documentation and stakeholder … Strong Python skills for backend services, SDKs, API development, authentication and testing. • Hands‐on experience working with LLMs, embeddings, prompt engineering, tool calling and RAG design. • Practical knowledge of GCP services including Vertex AI, Model Garden, BigQuery, Cloud Run and Google’s ADK. • Experience with document and data processing using ...

/B experiments and performance dashboards. • Integrate AI agent functionality with applications through MCP servers and reliable tool configurations. • Develop secure and scalable RAG pipelines, including ingestion, text processing, metadata handling and vector search in GCP. • Embed security, compliance, GDPR controls and best‐practice engineering with clear documentation and stakeholder … Strong Python skills for backend services, SDKs, API development, authentication and testing. • Hands‐on experience working with LLMs, embeddings, prompt engineering, tool calling and RAG design. • Practical knowledge of GCP services including Vertex AI, Model Garden, BigQuery, Cloud Run and Google’s ADK. • Experience with document and data processing using ...

equity & benefits Reports to: CTO Overview of the Role This is a rare opportunity to shape and lead the evolution of a next-generation, AI-native data platform within a high-growth, well-funded scale-up. As Director of Data Engineering, you will operate at the intersection … development of a knowledge graph and data enrichment pipelines to unlock proprietary data value Drive AI/ML Ops maturity , including LLM deployment, RAG pipelines, and evaluation frameworks Engineering & Architecture Define scalable, cloud-native architectures across GCP (preferred) and AWS Lead cross-cloud data orchestration , ensuring seamless data flow from ...

What You’ll Be Doing: Design and deliver full-stack, cloud-native AI applications across front end, APIs, and data layers Build and deploy RAG-based and agent-driven AI systems using secure, governed data sources Develop scalable services on Azure, integrating with enterprise platforms and data pipelines Implement MLOps … standards Main Skills Needed: Strong full stack engineering experience (React/TypeScript, Python, FastAPI, or Node.js) Proven experience building AI/ML systems, particularly RAG or agent-based architectures Solid Azure expertise (Azure ML, Azure OpenAI, Functions, AKS, CI/CD pipelines) Data engineering knowledge including pipelines, schema design ...

powered tools, systems and agents to streamline sourcing, research, diligence, and portfolio monitoring Design and deploy end-to-end LLM applications including research copilots, RAG systems, workflow automation, data enrichment, and deal intelligence tooling Ingest, clean, and analyse external datasets through scripts, pipelines, and lightweight ML components Integrate third-party … applied AI engineering, ML engineering, or forward deployed roles Strong Python Experience building and deploying LLM applications (OpenAI, Anthropic, Gemini, etc.) Deep familiarity with RAG methodologies, embeddings, and vector databases (Pinecone, Weaviate, pgvector) Robust API integration experience, including working with third-party datasets, web APIs, or scrapers A product mindset ...

powered tools, systems and agents to streamline sourcing, research, diligence, and portfolio monitoring Design and deploy end-to-end LLM applications including research copilots, RAG systems, workflow automation, data enrichment, and deal intelligence tooling Ingest, clean, and analyse external datasets through scripts, pipelines, and lightweight ML components Integrate third-party … applied AI engineering, ML engineering, or forward deployed roles Strong Python Experience building and deploying LLM applications (OpenAI, Anthropic, Gemini, etc.) Deep familiarity with RAG methodologies, embeddings, and vector databases (Pinecone, Weaviate, pgvector) Robust API integration experience, including working with third-party datasets, web APIs, or scrapers A product mindset ...

detection, and optimisation. The Role * Deliver full lifecycle AI and ML projects from prototype to production. * Build applied AI workflows including LLMs, NLP, and RAG-based solutions. * Work with large and messy tabular datasets to create high-impact models. * Develop classification and optimisation approaches to enhance customer outcomes. * Partner with … ecosystem. Your Skills and Experience * Strong commercial experience deploying AI and ML systems into production. * Hands-on experience with LLMs, NLP, or retrieval-augmented workflows. * Confident working with large-scale tabular datasets and complex data environments. * Cloud experience, ideally AWS, plus familiarity with MLOps practices. * Background ...

Experience Strong commercial experience using Python in applied AI or machine learning contexts Proven delivery of end-to-end AI solutions such as RAG systems, LLM-powered applications, or agent-based workflows Experience working closely with clients or end users, translating real requirements into technical solutions Solid software engineering fundamentals … including maintainable code, testing, and collaboration with engineering teams Practical knowledge of prompt engineering, RAG pipelines, agent workflows, and model evaluation Familiarity with modern GenAI tooling such as LangChain, LangGraph, or similar frameworks Motivation to work in a startup environment, with comfort around ambiguity, pace, and ownership What They Offer ...

GenAI workflows while working directly with users to shape how the product evolves. Key Responsibilities • Build end-to-end GenAI workflows using Python • Develop RAG pipelines and agent-based systems • Translate client requirements into production-ready solutions • Deliver POCs that evolve into scalable features • Collaborate with engineers on production deployment … Support demos and tailored client use cases Key Details • Salary: £65k–£90k • Working: Hybrid (3–4 days onsite, Holborn) • Stack: Python, LLMs, RAG, agents, LangChain/LangGraph • Visa: Cannot sponsor Interested? Please apply below. ...

enterprise-grade AI capabilities. What Youll Be Doing Designing and building Copilot solutions, intelligent agents, and LLM workflows Developing scalable AI components including RAG pipelines, embeddings, and vector search Integrating AI solutions into enterprise systems, APIs, and cloud platforms Conducting rapid prototyping to validate use cases, UX, and model performance … Essential Skills for the AI product developer Proven experience building solutions using LLMs, AI APIs, and Copilot Studio or similar tools Strong understanding of RAG architectures, vector databases, and embeddings Experience with Azure AI and cloud-native development Solid knowledge of secure engineering practices including authentication, data protection, and auditability ...

/Claude Code) Strong Plus Experience building agentic workflows that are trusted Experience with LangChain, LangGraph, or similar Experience building with vector databases, embeddings, RAG pipelines Experience with graph databases Experience building simulation, optimisation, or decision-support systems Prior startup or early-stage experience Why Join Us Work on problems … sustainability and your experience of designing data models, architecting platforms and building from zero to one? What do you think about the latest generation of coding LLMs - good, bad, what have you used ...

tactical edge. Own the deployment from infrastructure through to user acceptance. • Build bespoke capability on our platform. Extend our products with customer-specific workflows, RAG pipelines, agentic tooling, data connectors, knowledge graphs and reporting templates. Write production code. Ship it. • Close the loop with product engineering. Feed real operational insight … have seen what breaks between a notebook and a running service, and you know how to fix it • Practical experience with modern AI patterns: RAG, agentic architectures, evaluation, or fine-tuning of LLMs • Fluency with the modern deployment stack: containers, Kubernetes or equivalent, CI/CD, infrastructure-as-code ...

Work closely with stakeholders - listening, probing, and shaping solutions around real needs. Essential Experience Experience automating human-centric processes (approvals, performance workflows, document generation, analytics, etc.). Proven experience building AI agents and multi-step automation flows. Strong hands-on engineering skills (clean, explainable, well-structured code). … Expertise using ChatGPT Enterprise for workflow automation. Skilled in designing prompts, guardrails, and evaluation logic for reliable outputs. Experience building retrieval pipelines (RAG), vector search, or context-aware systems. Comfortable integrating AI systems with APIs and internal platforms. How to Apply If you're an AI Engineer ...

join at the foundational stage, working directly with world‐class engineers and product leaders to build the backend systems behind a next‐generation AI lifestyle platform. This product is already in the hands of deeply engaged early users, with engagement metrics far above industry norms. You will play … delivery of key features—from design to production rollout. Develop background processing systems, task queues, and agent orchestration. Work hands‐on with LLM integrations, RAG pipelines, and AI‐driven systems. Enhance system performance across SQL queries, APIs, and distributed jobs. Build and operate cloud infrastructure on GCP. Lead debugging ...

build a high-conversion sales pipeline. Al Revenue Ownership: Own the full lifecycle of Al Maas opportunities in international markets, from lead generation and qualification to solution design, commercial negotiation, and deal closure, driving growth in token consumption and revenue. Market & GTM Strategy Support: Track GenAl trends (foundation … pricing, and contracting, while collaborating with solution architects and product teams Cloud Experience: Familiar with cloud and AI infrastructure products (e.g., servers, GPU, MaaS, RAG, Agents); hands-on experience in cloud sales, business consulting, and operations. Mindset: Fast learner, customer-obsessed, results-driven, self-motivated, and passionate about Al innovation ...