26 to 50 of 241 LangGraph Jobs in England

TensorFlow . Deep understanding of LLMs, Generative AI, prompt engineering, RAG architectures and vector databases . Experience with frameworks and tooling such as LangChain, LangGraph or similar open-source AI toolkits . Experience fine-tuning, evaluating, deploying and monitoring large-scale AI systems. Strong understanding of MLOps and/ ...

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 ...

systems 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 and performance monitoring.Experience with ...

ability to apply them to real product challengesExperience with agentic AI frameworks and libraries in Python, such as AWS Bedrock AgentCore, LangChain/LangGraph, CrewAI, or the OpenAI Agents SDK, with an understanding of agent design patterns including tool use, orchestration, memory, and multi-agent workflowsAbility to own the full ...

ability to apply them to real product challenges Experience with agentic AI frameworks and libraries in Python, such as AWS Bedrock AgentCore, LangChain/LangGraph, CrewAI, or the OpenAI Agents SDK, with an understanding of agent design patterns including tool use, orchestration, memory, and multi-agent workflows Ability ...

ability to apply them to real product challenges Experience with agentic AI frameworks and libraries in Python, such as AWS Bedrock AgentCore, LangChain/LangGraph, CrewAI, or the OpenAI Agents SDK, with an understanding of agent design patterns including tool use, orchestration, memory, and multi-agent workflows Ability ...

Python, amongst othersExperienced in RAG Weaviate, OpenAI, Agents, MCP, Langchain, Prompt Engineering, Browser-Use, and DjangoExperienced building AI Tools, Agents and Agentic workflows (LangGraph, CrwAI)Hands-on Product building experience that cuts across the full SDLC - not just test automation and QE.Experienced in building RAG system with a nice ...

Generative AI and agentic AI systems — including LLM-powered application design, retrieval-augmented generation (RAG) architectures, and at least one agentic AI framework (e.g. LangGraph, LangChain, LlamaIndex, CrewAI) Experience designing and building data and context pipelines for AI systems — including embedding pipelines, vector databases, and semantic search applied to structured ...

Express or equivalentFrontend 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 ...

code, not just scripts (OOP, async, packaging, testing)Generative AI & LLM development — prompt engineering, fine-tuning, RAG pipelines, context window managementAgentic AI frameworks — LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflowsMachine Learning — model development, training, evaluation, and deploymentAPIs & backend development — FastAPI, REST APIs, microservices architectureVector databases & embeddingsCloud platforms ...

DevOps and business teams - Advise clients on AI platform capability and implementation strategy Tech environment: Python LLMs (prompt engineering, fine-tuning, RAG) LangChain/LangGraph Agent frameworks Vector databases MLOps/LLMOps AWS/Azure/GCP/Databricks Kubernetes & GPU infrastructure What you'll bring: - Experience designing enterprise ...

with engineering, data, DevOps and business teams to deliver end-to-end solutions.**Tech environment**Python, LLMs (prompt engineering, fine-tuning, RAG), LangChain/LangGraph, agent frameworks, vector databases, MLOps/LLMOps, AWS, Azure, GCP, Databricks, Kubernetes and GPU infrastructure.**What we're looking for**Proven enterprise ...

equivalent 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 ...

validate, evaluate, and improve AI-generated outputs; understanding of AI limitations and responsible use Familiarity with agentic system concepts — awareness of orchestration frameworks (LangChain, LangGraph, or equivalent), RAG pipelines, and how full-stack applications connect to agent-based architecture; production experience preferred, conceptual understanding required ...

enterprise environments Some experience working within engineering teams in agile, client-facing delivery contexts AI, data and technology awareness Practical experience with: Agentic frameworks: LangGraph, LangChain, CrewAI, Agentforce or similar Foundation model providers: Claude Code/Codex/Gemini, OpenAI or AWS Bedrock Vector databases: Pinecone, Weaviate, LlamaIndex or pgvector ...

capabilities on cloud platforms — such as Google Vertex AI Agent Builder, AWS Bedrock, or Azure OpenAIFamiliarity with agentic AI frameworks and tooling — such as LangGraph, LangChain, LlamaIndex, or CrewAI — and how they are appliedExperience with retrieval-augmented generation (RAG) architectures, vector databases, and LLM-powered applications as part ...

similar tools. Experience evaluating and adopting emerging technologies, including build-vs-buy decisions. Hands-on experience building AI agents using frameworks such as LangGraph, LangChain, or LlamaIndex. Experience implementing Retrieval-Augmented Generation (RAG) solutions and governance controls for enterprise AI applications. Experience using agentic AI to automate engineering workflows such ...

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 ...

models behave in production, not just in demos. Agentic Systems Design: Proven experience designing and deploying multi‐agent architectures and orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI); tool‐use patterns, human‐in‐the‐loop workflows, and agentic safety at enterprise scale. AI/ML Engineering & MLOps: Full AI/ML lifecycle ...

enterprise environments Some experience working within engineering teams in agile, client‐facing delivery contexts AI, data and technology awareness Practical experience with: Agentic frameworks: LangGraph, LangChain, CrewAI, Agentforce or similar Foundation model providers: Claude Code/Codex/Gemini, OpenAI or AWS Bedrock Vector databases: Pinecone, Weaviate, LlamaIndex or pgvector ...

environments Proven ability to lead engineering teams in agile, client-facing delivery contexts AI, data and technology awareness Deep practical experience with: Agentic frameworks: LangGraph, LangChain, CrewAI, Agentforce or similar Foundation model providers: Claude Code/Codex/Gemini, OpenAI or AWS Bedrock Vector databases: Pinecone, Weaviate, LlamaIndex or pgvector ...

models behave in production, not just in demos.* Agentic Systems Design:Proven experience designing and deploying multi-agent architectures and orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI); tool-use patterns, human-in-the-loop workflows, and agentic safety at enterprise scale* AI/ML Engineering & MLOps: Full AI/ML lifecycle ...

understand how models behave in production, not just in demos.Agentic Systems Design:Proven experience designing and deploying multi-agent architectures and orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI); tool-use patterns, human-in-the-loop workflows, and agentic safety at enterprise scaleAI/ML Engineering & MLOps: Full AI/ML lifecycle ...

resource optimisation highly desirable.Expert-level proficiency in Python, and modern AI/ML frameworks, including PyTorch, TensorFlow, and specialised Generative AI libraries (LangChain, LangGraph or related open-source toolkits strongly preferred. Background in Traditional ML/AI.Deep understanding of LLMs, prompt engineering, RAG pipelines, vector databases, and generative architectures; related ...

Vertex AI).Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic frameworks (LangChain, LangGraph, Semantic Kernel).Data pipelines: data lake/lakehouse architectures, ETL/ELT, and data quality/lineage tooling that feed AI systems.Automation, Orchestration & ObservabilityInfrastructure-as-code: Terraform ...