126 to 148 of 148 Retrieval-Augmented Generation Jobs in the UK excluding London

ideas to both technical and non‐technical audiences Nice to Have Research experience in areas such as large language models (e.g., training, fine‐tuning, RAG, evaluation, synthetic data generation), agentic AI, big data technologies, or digital twins Familiarity with emerging research and tooling ecosystems such as LangChain, LangGraph ...

used across the business. AI Software Engineer - Responsibilities Design and deliver practical AI solutions Build and maintain LLM-powered applications, including retrieval-augmented workflows and tools integrations Collaborate with product and engineering teams to embed AI capabilities into software suite Establish best practice and champion … Engineer Experience - delivering production-ready solutions using Python, TypeScript or C# Hands on experience building LLM-based applications and solid understanding of retrieval-augmented generation approaches Experience leading projects or parts of projects from design through delivery Product mindset and collaborative approach - able ...

Engineer/Data Scientist – Agentic AI – £100k + Hybrid – HealthTech/Clinical Workflows Python | LLMs | RAG | AI Agents | OpenAI | Copilot | Elasticsearch | Vector DBs | Java | JavaScript | SaaS | Hybrid | Do you want to build AI features embedded directly into real clinical workflows used by hospitals, within a business actively rolling out GenAI … value to clinical users. Joining their engineering team, you’ll play a key role in designing and building Agentic AI systems, leveraging LLMs and RAG architectures to create production-ready capabilities that integrate seamlessly into the product. • You’ll develop AI-driven workflows including automated summaries, letter generation ...

deploying production AI applications using LLMs Designing agentic workflows and multi-step AI pipelines Developing scalable backend APIs and cloud-native services Creating RAG pipelines, embeddings and AI retrieval systems Improving AI reliability through testing, evaluation and guardrails Working closely with engineering, product and business teams Contributing … architecture decisions and AI best practice Helping shape the future direction of AI capability across the business Tech environment Python, AWS, APIs, LLMs, RAG, Docker, Kubernetes, microservices, cloud-native architecture and modern AI engineering tooling. What they're looking for Strong Python backend engineering experience Experience building and deploying ...

data with advanced machine learning and synthetic intelligence. The Role Design, build, and deploy Generative AI and LLM-based solutions for synthetic data generation and data augmentation Develop and validate statistical and machine learning methodologies to ensure data quality, reliability, and trust Work closely with Product and Engineering … datasets and collaborating with engineering teams Confidence explaining methodology, limitations, and impact to a broad range of stakeholders Exposure to synthetic data, prompt engineering, RAG, or cloud-based data platforms is beneficial but not essential ...

team of engineers. Key Responsibilities * Lead the development and deployment of AI-powered tools to improve efficiency and productivity * Design advanced solutions including automation, RAG, and LLM-based workflows * Collaborate with stakeholders to identify and deliver strategic AI initiatives that deliver measurable business value * Provide guidance on AI architecture, tooling … with AI engineering, or software engineering (e.g. Python, Java, JavaScript/TypeScript etc.) with libraries/frameworks such as PyTorch, TensorFlow etc.) * Experience with RAG and LLM-based solutions * Solid understanding of AI architectures and data pipelines * Knowledge of security, compliance, and governance principles from a development perspective * Proven mentoring ...

reusable agent components and playbooks Proactively surface new automation opportunities across the business Key Skills Python & LLM agent frameworks (LangChain, CrewAI, LlamaIndex) Prompt engineering & RAG pipelines Business analysis & stakeholder management Process mapping & workshop facilitation Microsoft 365 & Microsoft Copilot No-code/low-code tooling (Zapier, Make) Desirable Skills Experience … etc. Strong enough technically to assess feasibility and scope what is buildable; commercially sharp enough to prioritise what is worth building. Familiarity with LLMs, RAG pipelines, tool/function calling, and integrating AI into real business workflows. Proven ability to lead discovery workshops and translate complex business problems into clear ...

Python development experience, ideally using modern backend frameworks Hands-on experience working with large language models and related techniques such as prompting, retrieval-augmented generation, or tool use Understanding of agent-based AI systems and orchestration approaches Good SQL skills and experience working with … beyond LLMs A proactive approach to experimenting with new AI tools and frameworks Apply now to play a key role in building next-generation AI capabilities within a high-performing engineering team. AI Engineer, Python, London, COR7586 Corriculo Ltd acts as an employment agency and an employment business. ...

Senior AI/ML Engineer (LLM's/RAG Pipeline Development)Guildford, Surrey (Fully Onsite)£85000 - £125,000 + 25% Bonus, 10% Pension, Private Medical.- Must have a Masters or PhD Degree in a STEM/Computing discipline.- Must work full-time, 5 days a week in the Guildford office. ...

solutions into real-world client environments. What You’ll Be Doing Owning and evolving our internal AI platform Building AI-powered client solutions: RAG pipelines, agent architectures, LLM integrations, protocol-driven tooling Designing internal AI tooling to accelerate delivery Leading advanced technical AI sessions within our upskilling programme Evaluating emerging … Essential: Strong software engineering foundations (clean code, testing, CI/CD, production mindset) Hands-on experience with LLMs (API integrations, prompt engineering, agent workflows, RAG systems) Experience shipping AI-powered features to production Proficiency in 2+ modern programming languages Familiarity with evolving AI tooling (MCP, A2A, Threads or similar) Consultancy ...

guide AI development Key Responsibilities Lead the development and deployment of AI-powered tools to improve efficiency and productivity Design advanced solutions including automation, RAG, and LLM-based workflows Collaborate with stakeholders and internal teams to identify and deliver strategic AI initiatives that deliver measurable business value and increase productivity … experience in AI engineering or software engineering Strong Python experience Proven experience of building and deploying AI solutions end-to-end Experience with RAG and LLM-based solutions, and with workflow design (e.g. N8N, Power Automate, LangChain, etc.) Solid understanding of AI architectures and data pipelines Knowledge of security, compliance ...

enterprise Agentic AI platforms. You will move beyond traditional software QA to build continuous safety pipelines, ensuring our non-deterministic LLM agents, RAG systems, and tool integrations are secure, resilient, and compliant before production release. Key Responsibilities Automated Adversarial Testing: Build and integrate automated red teaming suites into CI/… within FCA, DORA, or EU AI Act frameworks. AWS Bedrock Ecosystem: Hands-on experience configuring, testing, and bypassing Bedrock Guardrails, Agents, and Knowledge Bases (RAG) . AI Security & Fundamentals: Solid understanding of Foundation Models, tool use (function calling), OWASP LLM Top 10 , and NIST AI RMF . Automation Stack: Strong ...

hands-on engineering role focused on designing and maintaining scalable AI pipelines. You’ll work on real-world applications including document ingestion, RAG architectures, async workflows, structured outputs, and LLM orchestration in production environments. What we’re looking for: • Strong Python backend engineering skills • Experience shipping production LLM-powered systems … Hands-on with RAG, prompt engineering, and evaluation frameworks • Experience with OpenAI, Anthropic, or similar APIs • Comfortable owning systems end-to-end in a fast-moving environment Tech stack includes Azure, LLM pipelines, vector search, async processing, and API-first architecture. Hybrid role based near Guildford, UK. ...

various AI providers Tool Creation: Developing "Tools" (Function Calling) that allow LLMs to interact with real-world data, enabling features such as consultant lookups (RAG) and clinical system integrations Data Insights: Building pipelines to transcribe and analyse historical call recordings to extract sentiment, summary, and outcome data Prompt Engineering: Refining … understanding of JSON data structures AI/LLM Exposure: Practical experience interacting with LLM APIs (OpenAI, Anthropic, etc.) and understanding concepts like Context Windows, RAG, System Prompts, and Temperature Concurrency: Understanding of asynchronous programming (WebSockets, goroutines) is highly beneficial given the real-time nature of voice data Benefits: 25 Days ...

various AI providers Tool Creation: Developing "Tools" (Function Calling) that allow LLMs to interact with real-world data, enabling features such as consultant lookups (RAG) and clinical system integrations Data Insights: Building pipelines to transcribe and analyse historical call recordings to extract sentiment, summary, and outcome data Prompt Engineering: Refining … understanding of JSON data structures AI/LLM Exposure: Practical experience interacting with LLM APIs (OpenAI, Anthropic, etc.) and understanding concepts like Context Windows, RAG, System Prompts, and Temperature Concurrency: Understanding of asynchronous programming (WebSockets, goroutines) is highly beneficial given the real-time nature of voice data Several years experience ...

machine learning or software engineering environments. You will work on a broad range of AI challenges spanning multimodal AI, machine learning, computer vision, LLMs, RAG architectures, transformer models, audio processing and intelligent automation features within a highly collaborative engineering environment. Location: Cambridge, UK. Hybrid working model - minimum of 4 days … Kotlin, TypeScript and React, prior experience with these technologies is not required Interest and exposure across AI technologies such as machine learning, LLMs, RAG systems, computer vision, multimodal AI or transformer architectures Ability to work across both research/prototyping and production engineering Strong problem-solving ability and analytical thinking ...

party platforms Develop microservices, wrappers, connectors, and service interfaces to support solution components Support applied AI development including LLM services, speech services, classification models, RAG pipelines, and AI-enabled application features Prepare and maintain demo-ready technical builds for internal and customer-facing demonstrations Support the preparation of technical handoff … environment Excellent communication skills to articulate technical issues and blockers clearly Desirable Skills: Experience with AI/ML tools, LLMs, speech services, RAG systems, or AI APIs Experience with Unreal Engine, Unity, or other real-time 3D development environments Familiarity with Docker, FastAPI, REST APIs, Git, and deployment workflows Experience ...

operational software — turning fragmented operational data into structured, trusted intelligence. We're focused on difficult, practical problems: Text-to-SQL against real enterprise schemas RAG over messy operational data Screen recorded workflow mapping Workflow and knowledge tooling that operational teams will actually adopt The platform is being developed alongside … t. Tech you'll touch Laravel · Livewire · Alpine · Tailwind · Python · SQL Server (T-SQL) · PostgreSQL · Power BI/DAX · Docker · GitHub · LLM integrations · RAG · embeddings · Claude Code & Cursor daily Logistics Location: Fully remote, UK Hours: Full-time Type: Contract-to-perm. Outside IR35. Salary: £70,000–£80,000 on conversion ...

product challenges Responsibilties Design, build and deploy production-grade AI applications and services Develop intelligent workflows using LLMs, agentic architectures and orchestration frameworks Build RAG systems, knowledge retrieval platforms and AI-powered tooling Integrate AI applications with internal systems, business platforms and external services Develop scalable backend services … Your Experience Strong software engineering foundations Experience building and deploying AI products into production environments Python and modern backend engineering experience Experience with LLMs, RAG architectures and agentic AI systems MCP or similar protocols for connecting AI systems with tools and external services Strong product thinking and commercial awareness Experience ...

experimentation’s sake. Scope of Role Design, build and deploy AI-powered products and applications Develop production-grade LLM solutions and agentic workflows Build RAG architectures and knowledge retrieval systems Integrate AI applications with internal platforms, tools and business systems Identify opportunities where AI can create measurable commercial … Your Experience Strong software engineering foundations Experience building and deploying AI products into production environments Python and modern backend engineering experience Experience with LLMs, RAG architectures and agentic AI systems MCP or similar protocols for connecting AI systems with tools and external services Strong product thinking and commercial awareness Experience ...

client teams to design, build and deploy AI driven solutions on the platform Translate complex research and business questions into production ready LLM and RAG workflows Debug, optimise and scale LLM applications in real world, client facing environments Build and integrate data pipelines and services across cloud platforms and modern … Your Skills and Experience Strong commercial engineering experience in AI, machine learning or data focused roles Hands on experience with retrieval augmented generation and production LLM workflows Confidence debugging and improving end to end LLM systems in live environments Experience working with modern data ...

users ranging from highly technical teams to more non technical stakeholders Designing and building AI driven workflows, including LLM and retrieval augmented generation use cases Integrating knowledge graph data into customer environments using APIs, graph databases or analytical platforms Partnering with a solutions consultant … commercial experience building and deploying AI or LLM powered systems into production Hands on experience designing, building and debugging LLM workflows, including familiarity with RAG approaches Experience working with modern data platforms and warehouses such as Snowflake or BigQuery Exposure to graph databases and knowledge graphs is highly desirable, (Neo4J ...

Location Manchester, UK (Hybrid - 3 days per week in office) About ServisBOT ServisBOT is building the next generation of AI-driven enterprise automation for regulated industries — a secure, compliant SaaS platform where AI and humans work together to deliver outcomes our clients can trust. We partner with global … implementation in client environments and ensuring we deliver measurable value. You’ll also build confidence in key AI concepts like prompt engineering, LLMs, and RAG, helping translate customer needs into practical, trustworthy AI-enabled solutions. Key Responsibilities Problem Definition & Discovery Support discovery activities for product initiatives and customer engagements Help ...