1 to 25 of 615 Permanent LLM Jobs in England

platforms such as AWS, Azure ML and GCP AI Services. This role offers the opportunity to work on cutting-edge technologies in Generative AI, LLM fine-tuning, agentic orchestration, and vector databases, while shaping impactful consulting solutions across industries like Banking, Finance, and Capital Markets. Your Role As a Senior ...

working systems AI Engineering capability (essential) All engineers in this team are expected to meaningfully apply AI in production systems, including: Building and deploying LLM-based applications in production environments Designing agentic workflows and multi-step AI systems Implementing RAG (Retrieval-Augmented Generation) pipelines Working with OpenAI or Anthropic APIs ...

software engineering, or data engineering. Programming experience (especially Python) Experience writing clean, maintainable Python code. Applied AI experience such as exposure to LLM APIs (OpenAI, Azure OpenAI, Anthropic, etc.) and experience with small personal or internship projects building agents or AI-driven workflows. Agentic frameworks in Python is a plus ...

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 tuning techniques, security ...

Develop and deploy machine learning models for: Prediction Classification Automation Insight generation Support the full life cycle from experimentation through to production Generative AI & LLM Applications Develop AI-powered solutions using large language models (LLMs) Apply prompt engineering and context engineering techniques Build use cases such as: Chatbots Document processing ...

10+ years of professional software engineering experience with ownership of production systems 3+ years of hands‐on experience building and deploying AI/LLM‐based systems in production (agents, RAG pipelines, orchestration) Strong experience designing and delivering cloud‐native systems, including APIs, microservices, containers, and serverless or event‐driven architectures ...

development of AI solutions: design, build, test, and deploy models that are robust, scalable, and used by real users.Apply NLP and LLM techniques to solve real-world problems, ensuring models are optimized for performance and reliability.Continuously improve model quality through tuning, evaluation, and feedback from production usage.Evaluate third-party ...

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 ...

automated evaluation systems such as LLMasJudge and hybrid scoring approaches.‐based testing, regression suites, multi‐turn agent simulations, and automated evaluation systems such as LLM‐as‐Judge and hybrid scoring approaches.* Build, refine, and maintain frameworks that assess model quality, robustness, performance, safety, explainability, and reliability at scale.**Model Validation ...

JIRA Bonus points for: Knowledge/experience working with Cloud, preferably AWS Knowledge of AI/ML and latest AI trends & technologies Familiarity in LLM frameworks and libraries such as LangChain, Langfuse, LiteLLM CI/CD/Docker/Kubernetes Soft skills: Agile/SCRUM Strong technical, problem solving ...

mentor engineers within a collaborative team Your Responsibilities Lead technical delivery across machine learning and MLOps engagements Design, build, and deploy ML models and LLM-based solutions Develop and optimise pipelines for model training and deployment Work across cloud and high-performance computing environments Act as a subject matter expert ...

mentor engineers within a collaborative team Your Responsibilities Lead technical delivery across machine learning and MLOps engagements Design, build, and deploy ML models and LLM-based solutions Develop and optimise pipelines for model training and deployment Work across cloud and high-performance computing environments Act as a subject matter expert ...

mentor engineers within a collaborative team Your Responsibilities Lead technical delivery across machine learning and MLOps engagements Design, build, and deploy ML models and LLM-based solutions Develop and optimise pipelines for model training and deployment Work across cloud and high-performance computing environments Act as a subject matter expert ...

strategic concepts to diverse audiences, from engineers to executive leadership. Extensive experience designing, optimizing, and implementing strategic approaches to Model Context Protocols (MCP) for LLM-powered agents across multiple products, including advanced strategies for prompt engineering, context management, and memory architectures. Hands-on software engineering or data science experience, particularly ...

Responsibilities Lead client discovery sessions and pre-sales activities, proposal creation, identifying technology and AI opportunities and defining project scope Proven GenAI and LLM expertise, from RAG and fine-tuning to observability, focused on driving measurable business outcomes Advise on technology and architecture decisions, balancing cost, risk, and performance Advising ...

cross-functionally with Index R&D, Data & AI, and Engineering teams to ensure alignment between AI innovation and business priorities. Explore emerging technologies in LLM orchestration, multi-agent reasoning, and Model Context Protocol (MCP) to identify and adopt best practices for MSCI's AI ecosystem. Contribute to the evolution ...

Data Science and Platform Engineering, enabling rapid iteration while enforcing production and compliance standards. Responsibilities Design and implement Onsera's agentic AI platform – architect LLM/agent framework selection, standardized patterns for tools, memory, guardrails, evaluation, and observability Define MLOps protocols for agentic systems – environment separation, versioning of prompts, tools ...

CrewAI - not just conceptual Agentic Coding Tools Claude Code CLI, Cursor, OpenAI Codex, Copilot RAG & Vector Stores Chroma, Weaviate, Pinecone - knows where RAG breaks LLM APIs & SDKs Anthropic, OpenAI, Gemini - prompt design, tool use Python/TypeScript Primary languages for agent + backend development LangSmith/Observability Tracing, evaluation, debugging ...

infrastructure engineering role - not a data science or ML engineering position. You'll own the runtime, infrastructure, and operational layers that RAG pipelines, LLM orchestration, vector search, and evaluation workflows run on, across AWS and Databricks. The focus is on building scalable, observable, secure, and cost-efficient platform infrastructure that ...

adopt emerging AI and agent technologies. Hands-on experience with vector databases, embeddings, or prompt engineering. Understanding of AI fundamentals and experience using LLM APIs or AI-enhanced features and Agents. Experience with cloud services such as AWS, Azure, or serverless platforms. Interest in distributed systems, event-driven architectures ...

monitoring, and troubleshooting Data Science/Analytics Experience with data analysis using Python (pandas, numpy) Understanding of data pipelines and ETL processes AI/LLM Engineering Experience integrating LLM APIs (OpenAI, Anthropic, Gemini, or open-source equivalents) into production applications Understanding of core LLM concepts: context windows, token limits, temperature … thought, structured output, and instruction tuning Practical knowledge of RAG (Retrieval-Augmented Generation) architectures, including chunking strategies, vector embeddings, and similarity search Familiarity with LLM orchestration frameworks such as LangChain, LlamaIndex, or similar Experience designing and building agentic systems — tool-calling agents, multi-step reasoning, and human-in-the-loop ...

structured and unstructured. Description of the role The role will involve leading a team deploying forensic analytics (including testing routines across structured data and LLM-enabled unstructured, structured and open-source data analysis) over large datasets to help our clients solve their most complex fraud, misconduct and integrity matters. This ...

executives, to drive adoption and long-term success of Tungsten Automation solutions Production AI Experience : Leverage experience with deploying, monitoring, and maintaining AI/LLM models in production (e.g., Azure ML, AWS Sagemaker, or Kubernetes-based ML pipelines) Thought Leadership : Provide thought leadership on AI-driven automation trends and best ...

expertise across the Microsoft AI stack: Azure OpenAI Service, Azure AI Foundry, Semantic Kernel, Copilot Studio, Power Platform, and Microsoft 365. Strong understanding of LLM architectures, RAG patterns, agentic workflows, and prompt engineering. Experience delivering complex AI transformation programmes for clients in regulated industries. Demonstrated ability to translate technical ...

audit standards Champion scalable, secure, and efficient AI implementation. What We're Looking For Core Skills & Experience Strong experience in AI Engineering, ML/LLM applications, or intelligent automation Solid Java engineering background with production-quality coding practices Experience with CI/CD tools e.g., Jenkins, GitLab CI Hands ...