1 to 25 of 666 LLM Jobs in the UK

passion for building scalable, production-ready solutions. Key Responsibilities Design and build applied AI and machine learning solutions for client projects. Develop and deploy LLM-powered applications, RAG solutions, AI agents and workflow automation tools. Build and maintain scalable data pipelines, feature pipelines and model training workflows. Productionise ...

intelligent search and analysis. Ship production-grade AI features. Write clean, well-tested code (Python and/or TypeScript) to deliver production applications using LLM APIs, orchestration frameworks (e.g., LangChain, LlamaIndex), and CI/CD pipelines — from prototype through deployment and monitoring. Design evaluation and quality framework. Build automated evaluation ...

essential: 'strong general-purpose programming (most commonly Python) applied to AI/ML systems Semantic search, vector/embedding infrastructure, and RAG pipeline construction LLM orchestration and agentic frameworks (eg LangChain/LlamaIndex-style tooling, multi-agent patterns) Prompt engineering and systematic evaluation/guardrail tooling (hallucination detection, safety testing ...

essential: Strong general-purpose programming (most commonly Python) applied to AI/ML systems Semantic search, vector/embedding infrastructure, and RAG pipeline construction LLM orchestration and agentic frameworks (eg LangChain/LlamaIndex-style tooling, multi-agent patterns) Prompt engineering and systematic evaluation/guardrail tooling (hallucination detection, safety testing ...

tool-calling frameworks (e.g. LangGraph or equivalent), including familiarity with the Model Context Protocol (MCP) • Evaluation engineering (golden datasets, regression gates in CI, LLM-judge calibration) • Guardrail and AI-observability tooling (e.g. NeMo Guardrails, OpenTelemetry GenAI conventions, LangSmith, Braintrust) MLOps & LLMOps • Hands-on with MLOps platforms (Azure ML, Databricks, SageMaker ...

Cloud & Data Platforms – Microsoft Fabric, Databricks, Snowflake, Azure, AWS and GCP AI Technologies – GenAI frameworks, Agentic AI, vector databases, semantic search, knowledge retrieval and LLM application development Data & Visualisation – Power BI, Tableau, Looker and other business intelligence tools Consulting, Communication & Leadership: Ability to work effectively with both business and technical ...

into technical designs, prototypes, or working solutions Build or advise on ETL/ELT pipelines preparing diverse datasets for AI consumption Implement or guide LLM-based solutions, including RAG systems and automation scripts Develop or lead the design of Proof of Concepts to validate AI ideas Act as a technical ...

Cost Controls. Software Engineering: Clean Code (SOLID, DRY), DDD, modular architecture, TDD, code quality tools. · AI Engineering (Desirable): RAG pipelines, agentic workflows, MCP, LLM integration (OpenAI, Gemini or other models from Huggingface), LangSmith, TruLens. Agentic Frameworks (Desirable): LangChain, CrewAI, Autogen, OpenAI Agents, Google ADK. WHAT YOU'LL LOVE ABOUT WORKING ...

will be responsible for guiding a team of AI Engineers in the design, development, deployment, and operation of scalable AI and Large Language Model (LLM) powered applications. Working closely with Data Scientists, Product teams, and business stakeholders, you will ensure AI products are secure, reliable, and built to enterprise standards. … performing technical teams, creating a culture of collaboration, innovation, continuous improvement, and professional growth. Hands-on experience designing, building, and deploying Large Language Model (LLM) powered solutions and generative AI applications at enterprise scale. Strong Python development skills, with experience using machine learning frameworks such as PyTorch, TensorFlow, and Scikit ...

learning solutions. Work closely with stakeholders to understand business challenges and translate them into scalable data products. Develop and improve AI-powered solutions, including LLM and automation use cases. Drive best practices in model development, testing, monitoring and governance. Mentor colleagues and contribute to the wider technical direction ...

LLMOps practices: prompt and model versioning, automated evaluation, deployment pipelines and observability for AI workloads in production. Your Skills and Experience Production experience building LLM-based applications on Azure that went live and that you then supported, rather than proofs of concept that stopped at demo. Strong production coding ...

LLMOps practices: prompt and model versioning, automated evaluation, deployment pipelines and observability for AI workloads in production. Your Skills and Experience Production experience building LLM-based applications on Azure that went live and that you then supported, rather than proofs of concept that stopped at demo. Strong production coding ...

following: Data modelling experience including dimensional design, medallion architecture or source-to-target mapping Hands-on experience building pipelines that support agentic workflows or LLM-based applications Familiarity with data product principles: discoverability, reusability, quality contracts and SLAs Hands-on experience with Decision Intelligence Platforms (e.g. Palantir, Quantexa) Infrastructure ...

following: Data modelling experience including dimensional design, medallion architecture or source-to-target mapping Hands-on experience building pipelines that support agentic workflows or LLM-based applications Familiarity with data product principles: discoverability, reusability, quality contracts and SLAs Hands-on experience with Decision Intelligence Platforms (e.g. Palantir, Quantexa) Infrastructure ...

with the ability to engage senior stakeholders and lead technical discussions. Desirable Experience Experience with PyTorch, TensorFlow or other machine learning frameworks. Knowledge of LLM fine-tuning, model distillation and optimisation techniques. Experience with vector databases, semantic search, knowledge graphs or related technologies. Familiarity with AI governance frameworks, security standards ...

role in building and scaling asynchronous task pipelines, implementing MCP (Model Context Protocol) servers and tools around complex APIs and internal systems, and integrating LLM-based orchestration frameworks. On the front end, you'll build rich, data-dense interfaces using React and AG Grid. You will also work directly with ...

will be responsible for guiding a team of AI Engineers in the design, development, deployment, and operation of scalable AI and Large Language Model (LLM) powered applications. Working closely with Data Scientists, Product teams, and business stakeholders, you will ensure AI products are secure, reliable, and built to enterprise standards. … technical teams, creating a culture of collaboration, innovation, continuous improvement, and professional growth. \n Hands-on experience designing, building, and deploying Large Language Model (LLM) powered solutions and generative AI applications at enterprise scale. \n Strong Python development skills, with experience using machine learning frameworks such as PyTorch, TensorFlow ...

will be responsible for guiding a team of AI Engineers in the design, development, deployment, and operation of scalable AI and Large Language Model (LLM) powered applications. Working closely with Data Scientists, Product teams, and business stakeholders, you will ensure AI products are secure, reliable, and built to enterprise standards. … technical teams, creating a culture of collaboration, innovation, continuous improvement, and professional growth. \n Hands-on experience designing, building, and deploying Large Language Model (LLM) powered solutions and generative AI applications at enterprise scale. \n Strong Python development skills, with experience using machine learning frameworks such as PyTorch, TensorFlow ...

enterprise automation. What You'll Be Doing Designing and developing agentic AI systems capable of autonomous decision-making and task execution. Building sophisticated LLM-powered applications, orchestration frameworks, memory architectures, and tool-use capabilities. Developing custom AI workflows using large language models, retrieval systems, and multi-agent architectures. Collaborating closely ...

within the team, establishing the patterns other engineers follow and leaving clear documentation behind What We're Looking For Robust software engineering, including developing LLM-powered or agentic systems, and a track record operating at senior/lead level Strong engineering fundamentals: code that's clean, tested and built ...

within the team, establishing the patterns other engineers follow and leaving clear documentation behind What We're Looking For Robust software engineering, including developing LLM-powered or agentic systems, and a track record operating at senior/lead level Strong engineering fundamentals: code that's clean, tested and built ...

cross-functional teams to translate business requirements into technical AI solutions. Desirable Skills: Experience with LangChain, Semantic Kernel, Llama and related frameworks for building LLM-based applications. Familiarity with Model Context Protocol (MCP) and emerging standards for AI orchestration and context management. Experience designing and implementing RAG architectures in enterprise ...

cross-functional teams to translate business requirements into technical AI solutions. Desirable Skills: Experience with LangChain, Semantic Kernel, Llama and related frameworks for building LLM-based applications. Familiarity with Model Context Protocol (MCP) and emerging standards for AI orchestration and context management. Experience designing and implementing RAG architectures in enterprise ...

/ML systems in production Strong hands-on experience with semantic search, vector databases or embeddings, and building RAG pipelines Experience with LLM orchestration and agentic frameworks (e.g. LangChain, LlamaIndex or multi-agent patterns) Prompt engineering skills, plus experience with systematic evaluation and guardrail tooling, such as hallucination detection ...

handling large data volumes Develop and integrate APIs, microservices, and distributed systems Deploy and manage applications within Microsoft Azure environments Integrate applications with LLM-based services, Agentic AI workflows, and AI-driven platforms Work with containerised solutions using Docker and cloud-native deployment approaches Support and enhance CI/ ...