1 to 25 of 73 Remote/Hybrid LangGraph Jobs in England

experiment tracking, observability, model lifecycle management. Responsible AI : governance frameworks, guardrails, model safety, compliance, and auditability. Preferred but not required Orchestration frameworks : LangChain/LangGraph, LlamaIndex, CrewAI, AutoGen, DSPy, Semantic Kernel, Strands. Advanced retrieval : Graph RAG, knowledge graphs, context graphs, hybrid search, vector databases. Agentic patterns : multi-agent architectures, planning ...

solutions. Proficient in observability, performance optimization, security, and production reliability. Knowledge of Responsible AI, AI governance, compliance, and model risk management. Experience with LangChain, LangGraph, LlamaIndex, CrewAI, Semantic Kernel, or similar frameworks. Familiarity with vector databases such as Pinecone, Weaviate, ChromaDB, or pgVector. Experience implementing observability and monitoring solutions ...

development to model deployment, feature stores, model management and monitoring model management* Delivering solutions using the latest GenAI and Agentic Frameworks, such as ADK, Langgraph, Microsoft Agent Framework, Llamaindex and other* Translating AI use case requirements into data and AI architectures using the most suitable cloud services across hyperscalars* Leading ...

Architect AI, LLM Engineer, MLOps Engineer, AI Software Engineer, Django Developer, FastAPI Developer, React Developer, Next.js Developer, TypeScript Developer, Azure OpenAI, Vertex AI, LangChain, LangGraph, CrewAI, Autogen, OpenAI Agents SDK, Google ADK, RAG, retrieval augmented generation, MCP, LangSmith, TruLens, prompt engineering, Docker, Kubernetes, AKS, GCP, Azure DevOps, GitHub Actions, PostgreSQL ...

including version control, automated testing, and monitoring. Experience building or productionising 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 ...

ecosystems including OpenAI, Anthropic, Gemini, and related model platforms. Hands-on experience with RAG architectures, Agentic AI frameworks, and orchestration tools such as LangChain, LangGraph, AutoGen, and CrewAI. Proven experience applying Agile delivery, DevOps, MLOps, and LLMOps practices to enterprise AI programmes. Strong cloud architecture experience across Azure ...

inside large metadata-driven systems where behaviour is configured rather than coded. Desirable Experience with agent frameworks such as Semantic Kernel, Microsoft Agent Framework, LangGraph, AutoGen, PydanticAI, the OpenAI Agents SDK or CrewAI. Experience building reusable AI platforms, MCP ecosystems or shared engineering capabilities used across multiple products and teams. ...

/function calling, structured outputs, and model evaluation. Familiarity with tools or frameworks such as Git, REST APIs, SQL, Docker, LLM APIs, LangChain, LangGraph, LlamaIndex, or cloud AI services. Foundational understanding of responsible AI concepts, including data privacy, model limitations, human oversight, and safe AI deployment. Strong problem‐solving skills ...

production use cases including classification, summarisation, code generation, and autonomous decision-making. Experience designing and deploying agentic systems using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or equivalent — including multi-agent orchestration and tool-use patterns. Excellent engineering skills and strong understanding of Software Development Lifecycle, GitOps, and modern DevSecOps ...

grade agent connectivityDevelop RAG-based solutions, including GraphRAG and Agentic RAG, aligned with client requirementsWork with agent frameworks and SDKs such as Pydantic AI, LangGraph/LangChain or Microsoft agent platformsDefine evaluation strategies for agentic systems using automated and human-in-the-loop methodsImplement telemetry and observability solutions to monitor ...

involving multiple agents, models, tools and services. Experience with Azure, AWS or Google Cloud, Kubernetes, Helm, Terraform and CI/CD technologies. Experience with LangGraph, AutoGen, smolagents or similar frameworks. Experience with Model Context Protocol, model‐serving platforms, vector databases and LLM gateways. Experience implementing AI evaluation, observability, tracing ...

APIs, services, and data platforms. Strong and effective communication skills with experience engaging directly with business stakeholders. Desirable Experience Experience with Semantic Kernel, LangChain, LangGraph, AutoGen, CrewAI, or similar frameworks. Experience with vector databases, RAG architectures, and enterprise search solutions. Experience with MLOps, CI/CD, DevSecOps, and model lifecycle ...

systems through APIs, services, and data platforms. Strong and effective communication skills with experience engaging directly with business stakeholders. Experience with Semantic Kernel, LangChain, LangGraph, AutoGen, CrewAI, or similar frameworks. Experience with vector databases, RAG architectures, and enterprise search solutions. Experience with MLOps, CI/CD, DevSecOps, and model lifecycle ...

Proven ability to manage priorities well in a hybrid working environment Preferred criteria: Experience with LLM and agent frameworks (PydanticAI, DSPy, GEPA, LangChain/LangGraph, provider agent SDKs or similar), and an informed view of when to use them and when not Experience with evaluation and observability tooling such ...

using frameworks such as Next.js or Vite.* AI and Agentic Systems: Hands-on experience designing and deploying agentic architectures using frameworks such as LangChain, LangGraph, CrewAI, or the Anthropic Agent SDK, including tool use, MCP servers, and multi-agent orchestration.* LLM Experience: Practical, production experience with LLM providers (Anthropic, OpenAI ...

using frameworks such as Next.js or Vite.* AI and Agentic Systems: Hands-on experience designing and deploying agentic architectures using frameworks such as LangChain, LangGraph, CrewAI, or the Anthropic Agent SDK, including tool use, MCP servers, and multi-agent orchestration.* LLM Experience: Practical, production experience with LLM providers (Anthropic, OpenAI ...

TypeScript, using frameworks such as Next.js or Vite.AI and Agentic Systems: Hands-on experience designing and deploying agentic architectures using frameworks such as LangChain, LangGraph, CrewAI, or the Anthropic Agent SDK, including tool use, MCP servers, and multi-agent orchestration.LLM Experience: Practical, production experience with LLM providers (Anthropic, OpenAI, Mistral ...

model sees — retrieval strategy, memory, tool descriptions, and policy layers that constrain what an agent is allowed to do. Agent orchestration frameworks and standards (LangGraph, MCP, Temporal or equivalent), and experience with long-running or multi-step agent workflows. Observability and cost control for inference at volume. What success looks ...

hear from you! Proficiency in at least one programming language. I.e Python, C#, JavaScript, Kotlin, Java, Go.. Experience with Gen AI tools (e.g LangGraph, CrewAI, Hugging Face, OpenAI APIs etc) Experience in building and optimising systems for performance, scalability, and reliability Understanding of ML fundamentals (training, evaluation, deployment ...

multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems Experience designing and scaling low-latency ...

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 language processing (NLP) techniques, and the optimization of large ...

changing landscape of AI technologies. 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 language processing (NLP) techniques, and the optimization of large ...

Frontend Development**: Experience in building React applications using TypeScript, leveraging frameworks such as **Next.js** or **Vite**.* **GenAI Frameworks**: Familiarity with tools like **LangChain**, **LangGraph**, **CrewAI**, or **Vercel AI** (in Python or JavaScript).* **LLM experience**: Practical experience with **Large Language Models** (LLMs) such as **OpenAI**, **Anthropic**, **Mistral**, or **Llama ...

Frontend Development**: Experience in building React applications using TypeScript, leveraging frameworks such as **Next.js** or **Vite**.* **GenAI Frameworks**: Familiarity with tools like **LangChain**, **LangGraph**, **CrewAI**, or **Vercel AI** (in Python or JavaScript).* **LLM experience**: Practical experience with **Large Language Models** (LLMs) such as **OpenAI**, **Anthropic**, **Mistral**, or **Llama ...

more. Hands‐on experience with agents, not just prompted models. You have wired tools to a model and let it run multi‐step using LangGraph, AutoGen, Claude Agent SDK, OpenAI Assistants, or your own orchestration. Active, structured use of AI‐assisted development tools (Claude Code, Cursor, GitHub Copilot) with demonstrable ...