151 to 175 of 216 Retrieval-Augmented Generation Jobs in England

next-generation conversational AI and generative AI platforms. This role focuses on developing production-grade LLM applications, agent-based AI systems and RAG pipelines used in large-scale customer-facing environments. This is an opportunity to work on advanced AI assistant and conversational AI technology, building scalable multi … using modern AI frameworks. Key Responsibilities Design and build LLM-powered applications using Python and Generative AI frameworks Develop RAG (Retrieval Augmented Generation) pipelines and AI orchestration workflows Build and deploy agent-based AI systems using tools such as LangGraph, CrewAI or similar frameworks ...

Strong foundation in software development with C# and TypeScript. - Experience with AI/LLM concepts (e.g., prompt engineering, RAG). - Analytical mindset for assessing sufficiency (relevance, completeness, freshness) and mitigating risks like hallucinations. - Focus on Clean Architecture and Clean Code principles. Reasonable Adjustments: Respect and equality are core values ...

break into AI properly, not just talk about it? I'm working with a team building real world AI applications using LLMs and RAG and they're open to junior to mid-level developers who've already started exploring this space (even through personal projects) click apply for full ...

Strong foundation in software development with C# and TypeScript. - Experience with AI/LLM concepts (e.g., prompt engineering, RAG). - Analytical mindset for assessing sufficiency (relevance, completeness, freshness) and mitigating risks like hallucinations. - Focus on Clean Architecture and Clean Code principles. Reasonable Adjustments: Respect and equality are core values ...

Looking For Essential: Strong background in software engineering, architecture or technical delivery Clear pivot into AI, with hands-on understanding of LLMs, agent architectures, RAG and modern AI ecosystems Experience leading client AI or digital transformation engagements Consultancy or professional services background Ability to translate AI capability into commercial value ...

developing technical talent. Advise on internal AI platform strategy and client positioning. Apply modern AI/ML approaches, including LLMs, agent architectures, and RAG techniques, in delivery and practice strategy. Collaborate with stakeholders to translate technical capabilities into practical business impact. What We're Looking For: Essential: Strong background ...

done real AI work inside a high-calibre engineering organisation and worked closely with product. What you'll do Design and deploy LLM/RAG systems (GPT, Claude, Gemini) powering content generation, semantic search, and personalised learning experiences Build Knowledge Graph capabilities to underpin agentic workflows … Technically, you bring: Python fluency (NumPy, Pandas, Scikit-Learn, PyTorch) and solid TypeScript/API skills Hands-on experience with LLMs prompt engineering, evaluation, RAG architectures, safety considerations Cloud-native development on AWS and practical MLOps: CI/CD for models, version control, observability, retraining pipelines Familiarity with LangChain, Terraform ...

Model Development & AI Systems Design Design and train predictive models using AWS SageMaker Develop LLM-powered systems via AWS Bedrock (including Claude integration) Build RAG pipelines combining structured and unstructured data Develop evaluation frameworks for accuracy, bias, and robustness Apply best practices in feature engineering and experimentation 🤖 AI Agent & Workflow … practices AI-Native Tooling Foundation models for reasoning workflows Code-generation tooling for automation scripting Agent orchestration frameworks Enterprise workflow automation tools RAG architectures Embeddings & vector stores 👤 What We’re Looking For 6–10+ years in data science or applied ML Proven experience deploying ML models into production ...

Data & AI platforms (Azure AI, Vertex AI, Databricks, Hugging Face), advanced GenAI frameworks (LangChain, HF Transformers, LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI (RAG) for knowledge applications. GenAI ModelOps/MLOps & Governance: GenAI ModelOps/MLOps ...

Forward Deployed Engineer Generative AI/LLM Deployment GenAI | LangChain | RAG | AWS | Kubernetes | Customer-Facing We are hiring a Forward Deployed Engineer to lead the deployment of production-grade Generative AI and LLM solutions into enterprise environments. This is a hands-on, customer-facing role focused on building and deploying … RAG pipelines, multi-agent systems and fine-tuned LLM applications using tools such as LangChain and LangGraph. You will embed with client teams, own technical delivery from prototype to production, and demonstrate measurable KPI impact. Key Responsibilities Design and deploy GenAI/LLM applications (RAG, agentic AI, fine-tuning) Lead ...

controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures It Would Be Great If You Also Had Experience In Some Of These, But If Not Well Help You With Them Experience with advanced … techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) Familiarity with Infrastructure as Code (Terraform, CloudFormation) Experience with data processing frameworks (Spark, Dask) for large-scale ...

Senior LLM, RAG & Agentic AI Consulting Engineer - Lead/Senior FDE Remote First, some trips to client offices and HQ Lead the design and delivery of complex, AI-native client engagements, spanning agentic systems, retrieval architectures and semantic layers. This is a senior, hands-on consulting role combining … consulting engineering role. Candidates should bring: Solid experience in software engineering, AI engineering, or applied data engineering Strong hands-on experience with LLMs, embeddings, RAG, retrieval stacks and vector databases Experience designing or implementing multi-agent systems or tool-calling frameworks Strong Python skills with experience building production ...

Forward Deployed Engineer Generative AI/LLM Deployment GenAI | LangChain | RAG | AWS | Kubernetes | Client-Facing Were looking for a Forward Deployed Engineer to drive the implementation and rollout of enterprise-grade Generative AI and LLM solutions within production environments. This is a hands-on, customer-facing position focused on architecting … deploying RAG pipelines, agent-based systems, and fine-tuned LLM applications using frameworks such as LangChain and LangGraph. You will work closely with client teams, take full ownership of technical delivery from proof of concept through to production, and deliver measurable KPI-driven outcomes. Key Responsibilities Architect and implement GenAI ...

embedded teams with business stakeholders to rapidly deliver AI solutions to high-priority problems. Evaluating and integrating AI tools and frameworks (LLMs, vector databases, RAG, AI agents) into robust, scalable systems. Championing automation across the full AI lifecycle —from data ingestion and preprocessing to deployment and monitoring. Collaborating closely with … have Experience with tools such as LangChain, LlamaIndex, Haystack, Hugging Face, Weaviate, CrewAI, AutoGen , or similar. Hands-on work with Retrieval Augmented Generation , AI agents, and agent orchestration frameworks. Experience working with unstructured data (documents, conversations, images). Background in platform engineering, internal developer ...

capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. As a team: Our Advanced Technology Centre is a thriving technology and innovation hub from where we deliver high … streaming, batch, cloud, on-premises) using Azure, AWS, and GCP services. AI & ML Leadership Architect advanced Data Science, ML and AI solutions, including NLP, RAG LLM and Agentic AI systems. Oversee the implementation of MLOps frameworks, ensuring robust deployment, monitoring, and lifecycle management of ML models. Evaluate and recommend emerging ...

influencing the evolution of the company’s AI platform. What You’ll Be Doing • Architect and implement enterprise Generative AI solutions using LLMs, RAG pipelines, prompt engineering and frameworks such as LangChain • Design scalable AI systems using Azure OpenAI, OpenAI API, Claude, Bedrock or Vertex AI • Lead the architecture … Azure, or GCP) Experience designing large-scale distributed systems Previous experience in a Fintech/Payments environment Knowledge of Generative AI technologies, LLMs, RAG architectures, and ML deployment Familiarity with DevOps, CI/CD, and infrastructure as code Strong understanding of security architecture and enterprise system integration Excellent client-facing ...

Structure prompts for reliability, determinism, and auditability Build multi-step agent workflows using orchestration frameworks Develop autonomous and human-in-the-loop systems Implement RAG pipelines and memory-backed agents Build Enterprise-Grade Automation Deliver production workflows in Power Automate Connect AI agents to CRM, ERP, Finance, Support, and internal … standards and best practices Tech Environment AI & Agents Advanced reasoning models (e.g. Claude) Code generation models (e.g. Codex) Prompt engineering & evaluation frameworks RAG architectures Embeddings & vector search (desirable) Orchestration & Automation Agent orchestration frameworks (e.g. Antigravity) Power Automate API-first integrations Event-driven architectures Engineering Python REST APIs ...

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 ...

schema drift detection) Ensure alignment with governance, security and industry standards AI Enablement & Data Serving Build high-quality datasets for retrieval pipelines (RAG), embeddings and conversational agents Create data foundations supporting decision engines, reinforcement learning and value measurement Partner with AI engineers to operationalise pipelines for LLM workflows … modern Central London presence Comprehensive health, wellbeing and pension benefits This is an opportunity to help define how semantic data engineering enables next-generation AI systems, within a firm where clarity, technical depth and real-world outcomes matter. If you are an experienced Data Engineer ready to work ...

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 ...

business impact and ROI Present complex AI solutions to both technical and non-technical audiences Showcase innovation in GenAI, Responsible AI, and emerging architectures (RAG, vector search, embeddings) ✅ What We’re Looking For Proven experience in pre-sales, AI architecture, or technical bid writing Strong capability in scoping AI/… programmes and estimating effort Deep understanding of: Machine learning (supervised & unsupervised) Generative AI & LLMs Embeddings, vector databases, RAG MLOps and model lifecycle management Experience with platforms such as: Azure ML, AWS SageMaker, Google Vertex AI Databricks, LangChain, Hugging Face Ability to develop architecture artefacts (HLDs, solution diagrams, delivery models) Exceptional ...

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. ...

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 ...

Foundry environment. This is a hands-on role focused on building scalable, production-ready AI systems using LLMs, RAG (retrieval augmented generation), vector databases, embeddings and Azure AI services. Key Responsibilities Design and develop LLM-powered applications, AI agents and Copilot solutions Build … optimise RAG pipelines, embeddings and vector search Integrate AI solutions with enterprise systems, APIs and cloud platforms (Azure) Implement secure-by-design AI engineering, monitoring and observability Develop reusable components including prompt libraries, agent frameworks and connectors Prototype, test and improve model performance, reliability and scalability Key Skills Strong experience ...

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 ...