201 to 225 of 279 Retrieval-Augmented Generation Jobs in England

/or Python. C# is a bonus, not a blocker Hands-on with AWS, REST APIs, and PostgreSQL Experience building with LLMs: tool calling, RAG, embeddings, agentic workflows The kind of person who talks to users, understands the problem deeply, and ships with ownership High agency. Low ego. Obsessed with ...

enterprise environments Hands-on experience building agents or copilots using platforms such as Copilot Studio Experience working with generative AI concepts (e.g. prompt design, RAG, grounding) Good understanding of integration patterns (APIs, REST/JSON, event-driven workflows) Experience with Microsoft ecosystem tools such as Power Platform and Microsoft ...

SaaS, fintech, professional services or regulated environments Exposure to AI-enabled products, automation tools or GenAI initiatives Understanding of technologies such as LLMs, NLP, RAG pipelines or AI workflow tooling Strong stakeholder management and workshop facilitation skills Experience working in Agile product environments Commercially minded product thinking with a focus ...

value What We’re Looking For Experience delivering AI/GenAI solutions in a real business environment (not just demos) Strong understanding of LLMs, RAG, and workflow/automation patterns Ability to turn ambiguous problems into practical, shipped solutions Hands-on builder—comfortable prototyping, integrating tools, and iterating quickly Outcome ...

SaaS, fintech, professional services or regulated environments Exposure to AI-enabled products, automation tools or GenAI initiatives Understanding of technologies such as LLMs, NLP, RAG pipelines or AI workflow tooling Strong stakeholder management and workshop facilitation skills Experience working in Agile product environments Commercially minded product thinking with a focus ...

enterprise clients. We work with organisations to understand their workflows, identify where AI can automate or augment work, and build practical systems across LLMs, RAG, workflow automation, document intelligence, operational copilots, data extraction, and enterprise integrations. Our projects move quickly, so delivery is critical. We need someone who can help ...

working in regulated environments or with legal workflows. Thorough understanding of AI technologies used in legal environments (LLMs, NLP, extraction/classification models, summarisation, RAG pipelines, etc.) Hybrid Working Birketts is a flexible business which has embraced a hybrid working model where our colleagues enjoy a mix of home ...

offerings Ideal Background Active DV clearance Strong Python development experience in a production ML environment Experience with one or more of the following: RAG (including Graph RAG) Agentic AI systems and architectures Computer Vision/Vision Language Models Audio or multimodal AI Experience with Docker, Linux/Unix ...

will be involved across the full lifecycle of GenAI productsfrom proof of concept through to scalable production deployment and monitoring. Working with modern LLMs, RAG architectures and agentic frameworks , youll collaborate with data engineers, solution architects and business stakeholders to deliver secure, cost-effective AI solutions on AWS. Key Responsibilities … Design and implement production GenAI applications using LLMs (e.g. Anthropic, AWS Bedrock models) Build and deploy RAG systems using vector databases and semantic search Develop agentic AI workflows using frameworks such as LangChain, LangGraph, CrewAI or similar Create effective prompt engineering strategies with appropriate guardrails for production systems Implement monitoring ...

involved across the full lifecycle of GenAI products—from proof of concept through to scalable production deployment and monitoring. Working with modern LLMs, RAG architectures and agentic frameworks , you’ll collaborate with data engineers, solution architects and business stakeholders to deliver secure, cost-effective AI solutions on AWS. Key Responsibilities … Design and implement production GenAI applications using LLMs (e.g. Anthropic, AWS Bedrock models) Build and deploy RAG systems using vector databases and semantic search Develop agentic AI workflows using frameworks such as LangChain, LangGraph, CrewAI or similar Create effective prompt engineering strategies with appropriate guardrails for production systems Implement monitoring ...

solving some of the most exciting challenges and problem solving in enterprise AI rollout, spanning enterprise data pipelines, multi-agent orchestration/workflows and RAG/SLM finetuning. Responsibilities Lead the technical solution design and implementation of large-scale Agentic and Knowledge AI solutions for key enterprise clients. … solution delivery through reusable assets, frameworks, and documentation. Champion observability, monitoring, versioning and telemetry to ensure trustworthy and auditable AI agents. Stay current on RAG, LLM/SLM advancements, Agentic AI tooling, vector/graph databases, retrieval optimizations, multi-modal systems, evaluation frameworks, GPU/Infra trends, fine ...

major projects, with high-impact, end-to-end ownership. What you'll be doing Build and deploy LLM-based applications , including RAG systems, chatbots, and agentic workflows Apply traditional ML techniques (e.g. regression, classification, gradient boosting) where appropriate Design and deliver end-to-end AI systems from discovery to production … product teams, and senior stakeholders across the business Tech stack Python & SQL (essential) GCP (preferred, but flexible depending on experience) LLMs/GenAI/RAG/agentic frameworks (LangChain, LlamaIndex etc.) MLOps tools: Git, CI/CD, Docker, Kubernetes, APIs What you bring Core requirements 5+ years in data science ...

experience with Docker, Linux/Unix CLI, Git, and testing Understanding of modern AI approaches, including: Agentic AI systems RAG (Retrieval Augmented Generation) Graph-based approaches Computer vision, audio, or multimodal models Knowledge of data governance and security best practices Strong communication and problem … solutions in secure environments High-performance computing and cloud-native AI architectures End-to-end MLOps lifecycle and model management Advanced AI techniques including RAG, agentic systems, and multimodal models Secure, high-assurance data environments Modern DevOps, CI/CD, and engineering practices Why Join? Work at the forefront ...

experience with Docker, Linux/Unix CLI, Git, and testing Understanding of modern AI approaches, including: Agentic AI systems RAG (Retrieval Augmented Generation) Graph-based approaches Computer vision, audio, or multimodal models Knowledge of data governance and security best practices Strong communication and problem … solutions in secure environments High-performance computing and cloud-native AI architectures End-to-end MLOps lifecycle and model management Advanced AI techniques including RAG, agentic systems, and multimodal models Secure, high-assurance data environments Modern DevOps, CI/CD, and engineering practices Why Join? Work at the forefront ...

experience with Docker, Linux/Unix CLI, Git, and testing Understanding of modern AI approaches, including: Agentic AI systems RAG (Retrieval Augmented Generation) Graph-based approaches Computer vision, audio, or multimodal models Knowledge of data governance and security best practices Strong communication and problem … solutions in secure environments High-performance computing and cloud-native AI architectures End-to-end MLOps lifecycle and model management Advanced AI techniques including RAG, agentic systems, and multimodal models Secure, high-assurance data environments Modern DevOps, CI/CD, and engineering practices Why Join? Work at the forefront ...

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 ...

multi-modal LLMs (text, image, audio, video), design agentic workflows enabling AI agents to interact with data sources and APIs using prompt engineering and RAG, optimise and deploy large language and multi-modal models with a focus on performance and latency and build scalable MLOps pipelines and full-stack applications … frameworks, Langfuse, Langsmith, MCP (Model Context Protocol), bias mitigation techniques Apply now to find out more about this Senior AI Engineer (Python LLM MLOps RAG MCP) opportunity. ...

/or data platforms at scale Experience in a senior technical or leadership role (3+ years) Strong understanding of modern AI approaches, including LLMs, RAG, and orchestration Knowledge of cloud environments, security, and compliance considerations Morgan Hunt is a multi-award-winning recruitment business for interim, contract and temporary recruitment ...

delivering innovative machine learning solutions: Building and deploying LLMs and ML models (cloud or HPC) Leading technical delivery across projects Driving adoption of GenAI, RAG, and agent-based systems Acting as the SME for ML engineering and deployment Tech Focus Python, Docker, Linux, Git AWS or Azure CI/… MLOps pipelines Exposure to RAG, computer vision, or multimodal AI Why Apply? Work on next-generation AI use cases Strong focus on innovation and career progression Opportunity to lead and shape technical direction Security clearance eligibility required. ...

their data needs and unblock them quickly. Bring AI Into Your Own Workflow: Use AI tooling to accelerate your own engineering, from code generation to pipeline documentation to data quality checks. Team & Operations Share What You Know: Champion knowledge sharing and best practice across the team and wider … Experience with Terraform or equivalent infrastructure-as-code tooling. Familiarity with statistical, ML or AI concepts, and ideally with building data layers that feed RAG pipelines, agents, or LLM-based applications. Comfort with vector databases, embeddings or semantic search is a plus. Working knowledge of Google's marketing stack: Google ...

sources, shapes and wins deals. First hire in, you set the technical direction, the patterns and the bar. What you'll actually build • Production RAG and agentic systems over deal docs, sponsor data and market intel • LLM pipelines with real grounding, evaluation, citation traceability and refusal logic, not chatbots that … data, integrations, the UI the deal team actually uses Stack Python, Java/.NET, SQL, Azure (preferred), Kafka, microservices, Docker, CI/CD LLMs, RAG, vector DBs (Pinecone, pgvector, etc.), LangChain/LangGraph, embeddings, fine-tuning (LoRA/QLoRA welcome) Bonus: Kubernetes, DealCloud or Salesforce integration What we need from ...

include AI sales assistants, underwriting automation, internal summarisation systems, and workflow efficiency tools. Key Responsibilities • Build and deploy production-grade AI applications • Develop LLM, RAG, and agentic AI systems • Deploy applications into GCP environments • Work closely with cross-functional business stakeholders • Improve scalability, reliability, and AI deployment workflows • Build APIs … days per week in London office • Contract: 12-month FTC (maternity cover) • Tech stack: Python, GCP, APIs, Docker, Kubernetes, CI/CD, LLMs, RAG, LangChain/LlamaIndex • Sponsorship: Cannot sponsor Interested? Please apply below. ...

this is the clearest indicator of someone who has shipped LLM systems in production. • Deep, current LLM engineering practice. System-level prompt design, RAG, structured generation, fine-tuning trade-offs (SFT, DPO, LoRA), and working knowledge of the frontier model landscape. • LLM safety and security. Prompt injection mitigation ...

memory patterns • Lead solution design using Generative AI and LLM ecosystems, including: o Prompt engineering and prompt pipelines o RAG (Retrieval Augmented Generation) architectures o Model fine tuning and evaluation strategies • Provide technical oversight and mentoring to engineering and data science teams Enterprise … solutioning efforts Technical Expertise • Strong hands on experience with: o Large Language Models (LLMs) and GenAI platforms o Agentic frameworks and orchestration patterns o RAG pipelines, vector databases, and embeddings • Experience across major AI ecosystems (e.g., cloud AI platforms, open source LLM tooling) • Solid understanding of data engineering, 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 ...