1 to 25 of 2,433 LLM Jobs in England

grade Generative AI applications, including:* Retrieval-Augmented Generation (RAG)* AI Agents and Agentic Workflows* Prompt Engineering and Prompt Optimization* Model Evaluation and Observability Frameworks* LLM Fine-tuning and Adaptation Techniques* Hands-on experience with Azure AI Foundry, Azure OpenAI Service, Model Context Protocol (MCP), and modern AI orchestration frameworks.* Strong ...

understanding of the distinction between Generative AI and Agentic AI, including their foundations, capabilities, and appropriate use cases. Strong understanding of AI, ML and LLM concepts, including prompt engineering, prompt grounding, iterative loop techniques, context windows, embeddings, RAG, agentic workflows. Proven ability to integrate AI capabilities both into low-code ...

frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ADK, or similar.* Ability to design and implement RAG pipelines, agentic workflows, MCP and integration with LLM APIs (OpenAI, Anthropic, Hugging Face OR similar).* Proficiency in CI/CD and containerisation: GitHub Actions, Azure DevOps, Docker, Kubernetes. **Nice to haves:*** Familiarity ...

frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ADK, or similar. Ability to design and implement RAG pipelines, agentic workflows, MCP and integration with LLM APIs (OpenAI, Anthropic, Hugging Face OR similar). Proficiency in CI/CD and containerisation: GitHub Actions, Azure DevOps, Docker, Kubernetes. Nice to haves Nice ...

date on market trends, new opportunities, and the changing landscape of AI technologies. Requirements Experience AI Orchestration & Development: Expert-level experience building complex LLM‐powered systems and multi‐agent workflows using frameworks like LangGraph, LangChain, AutoGen, or ADK. Artificial Intelligence & Machine Learning: Deep practical understanding of machine learning algorithms, natural ...

date on market trends, new opportunities, and the changing landscape of AI technologies. Requirements Experience AI Orchestration & Development: Expert-level experience building complex LLM-powered systems and multi-agent workflows using frameworks like LangGraph, LangChain, AutoGen, or ADK. Artificial Intelligence & Machine Learning: Deep practical understanding of machine learning algorithms, natural ...

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 (e.g. LangChain/LlamaIndex‐style tooling, multi‐agent patterns) Prompt engineering and systematic evaluation/guardrail tooling (hallucination detection, safety testing ...

encompassing:Compute & Services: Java, .NET, Python, Cloud-native microservicesData & Analytics: Databricks, Microsoft Fabric, AWS Glue, Athena, Event Streaming (e.g., Kafka)AI & ML: Azure OpenAI, LLM Integration patterns, Vector DatabasesIntegration & Storage: Azure Data Factory (ADF), SQL Server, Enterprise relational platformsInfrastructure: Azure, AWS, and Hybrid Cloud networksCandidates are not expected ...

field, or demonstrable relevant experience. Additional desired skills Knowledge of vector databases and retrieval strategies. Experience with recommender systems and ranking models. Familiarity with LLM evaluation tools (e.g., RAGAS, TruLens, LangSmith, Arize). A working understanding of cloud networking and platform infrastructure. Experience in e‐commerce or retail environments. ...

agentic AI systems—tool use, orchestration, multi‐step reasoning, or agent frameworks (e.g. LangGraph, LangChain, CrewAI, AutoGen, or similar). Experience with GenAI/LLM systems in a production context (RAG, prompt orchestration, evaluation, guardrails, cost/latency optimisation). Exposure to MCP (Model Context Protocol) and tool‐based/ ...

date on market trends, new opportunities, and the changing landscape of AI technologies. Requirements Experience AI Orchestration & Development: Expert-level experience building complex LLM-powered systems and multi-agent workflows using frameworks like LangGraph, LangChain, AutoGen, or ADK. Artificial Intelligence & Machine Learning: Deep practical understanding of machine learning algorithms, natural ...

application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scale Implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration Make key technical decisions while remaining accountable ...

application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scale Implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration Make key technical decisions while remaining accountable ...

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 ...

application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real‐time and batch AI workloads at enterprise scale Implement advanced large language model applications using retrieval‐augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration Make key technical decisions while remaining accountable ...

application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scale Implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration Make key technical decisions while remaining accountable ...

application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scale Implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration Make key technical decisions while remaining accountable ...

Solution Design: Design, build, and maintain scalable AI architectures and pipelines that support business requirements, ranging from predictive modelling to Generative AI applications. LLM Integration: Operationalise Large Language Models (e.g., GPT, Llama, Mistral) and NLP workflows (BERT, topic modelling) for production environments. Agentic & Multi-Agent Systems: Design and orchestrate autonomous ...

Django, Flask, or FastAPI Experience with API development, integration, and web services in production environments Hands‐on experience integrating AI or ML models, LLM APIs, or automation frameworks into applications Strong knowledge of database systems including SQL, NoSQL, and data storage patterns for AI applications Familiarity with cloud platforms such ...

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 ...

RBAC and cost controls. Solid software engineering fundamentals: Clean Code (SOLID, DRY), DDD, modular architecture, TDD and code quality tooling. Desirable: RAG pipelines, MCP, LLM integration (OpenAI, Gemini, Hugging Face models), LangSmith, TruLens, and agentic frameworks such as LangChain, CrewAI, Autogen, OpenAI Agents and Google ADK. You won’t need ...

RBAC and 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 HEREWe ...

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 ...

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 ...

intersection of Data Engineering, AI and Generative AI , giving you the opportunity to work across modern data platforms, scalable data pipelines, machine learning and LLM-enabled solutions. You must currently come from, or have recent experience working within, a consultancy or professional services environment , with experience delivering technical solutions directly ...