51 to 75 of 2,433 LLM Jobs in England

enterprise applications. Strong knowledge of Microsoft Azure, including Azure AI Foundry, Azure AI Services and cloud-native application development. Experience implementing AI solutions including LLM integration, prompt engineering, Retrieval-Augmented Generation (RAG) and vector databases. Experience working with SQL and NoSQL databases, with knowledge of platforms such as SQL Server ...

DevOps: Experience with Kubeflow, Docker, Kubernetes, and Linux environments. CI/CD: Proficiency in building and managing continuous integration and deployment pipelines. GenAI/LLM: Experience with LLMs, GenAI APIs, Model Garden, and GenAI Studio. Good to Have Experience with AlloyDB and enterprise database solutions. Familiarity with PaLM embeddings ...

OpenAI Agents SDK, AWS Bedrock AgentCore, Microsoft Agent Framework/Semantic Kernel. Framework choice follows the engagement; the discipline is the same. Models: Multi-LLM via the kit (e.g. Claude on Bedrock, Gemini, Azure OpenAI), selected per use case for quality, latency and cost. Interfaces: Tools and Model Context Protocol ...

OpenAI Agents SDK, AWS Bedrock AgentCore, Microsoft Agent Framework/Semantic Kernel. Framework choice follows the engagement; the discipline is the same. Models: Multi-LLM via the kit (e.g. Claude on Bedrock, Gemini, Azure OpenAI), selected per use case for quality, latency and cost. Interfaces: Tools and Model Context Protocol ...

thought leadership. What we’re looking for Deep software/systems engineering (Python/TypeScript, distributed systems, CI/CD). Applied‐AI expertise: LLM/RAG engineering; evaluation; telemetry/drift monitoring; versioning and release management. Cloud architecture (Azure/AWS/GCP), Kubernetes/Docker, serverless ...

Systems, or a related field, or equivalent practical experience. Machine Learning: Expertise in time‐series forecasting, clustering, and correlation algorithms. Generative AI: Experience with LLM prompting, Retrieval‐Augmented Generation (RAG), and LangChain. Cloud Infrastructure: Deep understanding of AWS, Azure, or GCP infrastructure components Additional Preferred Qualifications: Experience with enterprise observability ...

pipelines for infrastructure and applications Agent Engineering & Development: 1+ years of experience building production AI/ML applications or agents Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications Experience with state management patterns (short-term and long-term memory) Experience designing and implementing evaluation ...

taking AI prototypes to production in enterprise environments. Education: BS in Engineering, Computer Science or equivalent; advanced degree preferred. Agentic AI/LLMs: LLM orchestration, prompt engineering, context‐window management and production guardrails; MCP, tool‐augmented agents and RAG at enterprise scale. Enterprise integration: Integrating AI into enterprise systems ...

agents using Python; experience with APIs, event-driven workflows, testing, source control, CI/CD and operational support Practical knowledge of agent architectures, LLM applications, RAG, tool calling, memory, orchestration, multi-agent patterns, MCP/A2A concepts and associated security risks Hands-on experience with security monitoring, detection engineering, incident ...

Description AI Large Language Model (LLM) Technology Architect Career Level: Associate Manager/Specialist Location: London YOU ARE As a hands-on AI/LLM Architect, you will be at the heart of designing and building advanced AI systems that power the modern enterprise. This is a deeply technical, hands … cloud vendor. Practical experience in the Agentic,LLMand Generative AI space. Well versed in coding using python Solid foundation in architecting and operationalizing LLM driven application architecture patterns. Professional working experience in coding engineering, machine learning, deep learning and NLP solutions and applications. Several years of hands on experience ...

Apply? Work on high-profile AI transformation programmes. Design and build enterprise-scale AI solutions. Exposure to the latest GenAI, Agentic AI and LLM technologies. Opportunity to influence architecture, engineering standards, and AI strategy. Flexible location options across the UK. If you're passionate about building production-grade AI solutions ...

strategic AI platform partnerships (e.g., Google, Anthropic), third‐party tooling, and outsourced delivery models Qualifications 15+ years of experience in Technology – Required: Generative AI & LLM Engineering: Deep, hands‐on expertise in large language models including model selection, fine‐tuning, prompt engineering, retrieval‐augmented generation (RAG), vector database design, and evaluation ...

strategic AI platform partnerships (e.g., Google, Anthropic), third-party tooling, and outsourced delivery models## **Qualifications:****15+ years of experience in Technology - Required:*** Generative AI & LLM Engineering: Deep, hands-on expertise in large language models including model selection, fine-tuning, prompt engineering, retrieval-augmented generation (RAG), vector database design, and evaluation ...

ReqID: FEQ427R340 Location: London Skills: Data Science, Machine Learning, AI, LLM, GenAI Mission As a Senior Specialist Solutions Architect (ML & AI), you will serve as the trusted technical ML and AI expert for Databricks customers and the Field Engineering organization. You will partner with Solution Architects to guide enterprise ...

users. Our ML team works end-to-end, from R&D to deployment, across traditional ML, deep learning, data engineering, foundation models and LLM/agentic systems. We are now hiring across a broad range of ML skills, including model training, evaluation, optimisation, infrastructure and deployment. As an ML Engineer ...

STEM discipline, or equivalent professional experience.Strong experience developing AI solutions using Python and modern AI frameworks such as LangChain or similar technologies.Deep understanding of LLM architectures, Generative AI, Agentic AI concepts, RAG frameworks, embeddings, and prompt engineering.Experience designing and deploying solutions on Azure, AWS, or GCP cloud platforms.Experience working ...

engineering domains. End‐to‐end exposure in model lifecycle development, including extensive experience training and deploying ML models in production environments. Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns. Experience in fine‐tuning LLMs for domain‐specific enterprise applications. Strong expertise in MLOps and LLMOps, ensuring scalable ...

branching strategy, automated testing, environment management Solid statistical foundations Insurance experience, ideally Lloyd's or London Market, is a big plus. So is deploying LLM based solutions, PySpark or Power BI. Permanent, up to £90,000 plus 20% bonus, three days a week in the office in the City. #J ...

engineering domains. End-to‐end exposure in model lifecycle development, including extensive experience training and deploying ML models in production environments. Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns. Experience in fine‐tuning LLMs for domain‐specific enterprise applications. Strong expertise in MLOps and LLMOps, ensuring scalable ...

optimize retrieval, and drive data‐driven decision‐making; conduct A/B tests and performance evaluations. Mentor and guide team members on agent frameworks, LLM usage, safety, and best practices. Required Qualifications, Capabilities, and Skills: Advanced degree in Computer Science, Data Science, Machine Learning, or related field. Experience building ...

optimize retrieval, and drive data-driven decision-making; conduct A/B tests and performance evaluations. Mentor and guide team members on agent frameworks, LLM usage, safety, and best practices. Required Qualifications, Capabilities, and Skills Advanced degree in Computer Science, Data Science, Machine Learning, or related field. Experience building ...

production. High proficiency in at least one modern language: Python, JavaScript/TypeScript, Java, or Apex. Hands‐on AI & Grounding Expertise: Deep experience with LLM orchestration, prompt tuning, and building RAG pipelines, vector search indexes, and knowledge base retrievers for enterprise data. Multi‐Agent Systems & API Mastery: Practical experience with ...

with multiple modern programming languages including Python, Golang, TypeScript and similar technologies in an AWS/Cloud environment Experience in the use of GPT, LLM, RAG, Gen AI, Prompt Engineering related technologies Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming ...

cloud data platforms, distributed processing, data modelling, and analytics/BI consumption patterns Exposure to AI/ML engineering practices, feature pipelines, model productionization, LLM‐based applications, or agentic AI patterns will be an added advantage Experience with DevOps and DataOps practices, including CI/CD, monitoring, observability, and incident ...

OpenAI Agents SDK, AWS Bedrock AgentCore, Microsoft Agent Framework/Semantic Kernel. Framework choice follows the engagement; the discipline is the same. Models: Multi-LLM via the kit (e.g. Claude on Bedrock, Gemini, Azure OpenAI), selected per use case for quality, latency and cost. Interfaces: Tools and Model Context Protocol ...