26 to 50 of 193 LangGraph Jobs in England

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 ...

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 scaleAI/ML Engineering & MLOps: Full AI/ML lifecycle ownership ...

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 ...

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 & Observability ...

React applications using TypeScript. Familiarity with frameworks such as Next.js, Vite, or similar. Generative AI Technologies Experience with Generative AI frameworks such as LangChain, LangGraph, CrewAI, Vercel AI, or equivalent tools. Practical experience working with Large Language Models (LLMs), including platforms such as OpenAI, Anthropic, Mistral, Llama, or similar. Familiarity ...

vector databases, knowledge graphs and prompt engineering Experience building multi‐step LLM workflows and agentic systems using frameworks (e.g. SDK, Strands, Claude Agents SDK, LangGraph, etc.) or custom implementations where needed Strong Python (or other modern programming language) proficiency with production API/service development experience and cloud platform knowledge ...

React applications using TypeScript. Familiarity with frameworks such as Next.js, Vite, or similar. Generative AI Technologies Experience with Generative AI frameworks such as LangChain, LangGraph, CrewAI, Vercel AI, or equivalent tools. Practical experience working with Large Language Models (LLMs), including platforms such as OpenAI, Anthropic, Mistral, Llama, or similar. Familiarity ...

distributed systems, microservices, or complex backend APIs that support AI/agent workflows. Solid expertise with systems that integrate AI models, agent frameworks (e.g., LangGraph, Agent Harness or platform-specific tooling), vector databases, and large context reasoning services. Understanding of agent orchestration patterns, state management, and asynchronous workflows. Experience with ...

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 ...

learning - gain hands-on experience with cloud platforms, AI technologies, middleware systems, and modern engineering practices Core Technologies Python Java Go AI - LLM Frameworks (LangGraph, LangChain, Agent Frameworks) AWS - GCP - Azure Kubernetes - Docker Terraform - Ansible Jenkins Prometheus - Grafana - Splunk Kafka - Flink Spring Boot Tomcat IBM MQ DataPower Linux - Unix What ...

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 ...

U.S., Europe, India, and SingaporeContinuous learning – gain hands-on experience with cloud platforms, AI technologies, middleware systems, and modern engineering practicesCore TechnologiesPythonJavaGoAI - LLM Frameworks (LangGraph, LangChain, Agent Frameworks)AWS - GCP - AzureKubernetes - DockerTerraform - AnsibleJenkinsPrometheus - Grafana - SplunkKafka - FlinkSpring BootTomcatIBM MQDataPowerLinux - UnixWhat You'll DoBuild Production-Grade SoftwareDesign and develop scalable automation platforms ...

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 ...

projects. using evidence-based methods to assess impact/improve scalability. Expertise across orchestration/governance/development tools such as LangChain/LangGraph/Azure Foundry/Azure AI/MCP/Python/vector databases. Experience providing effective 1st/2nd/3rd line support across multiple business ...

serving and gateway infrastructure (e.g. vLLM, LiteLLM, managed endpoints), with routing, failover, and per-workload cost attribution• Agent orchestration and tool-calling frameworks (e.g. LangGraph or equivalent), including familiarity with the Model Context Protocol (MCP)• Evaluation engineering (golden datasets, regression gates in CI, LLM-judge calibration)• Guardrail and AI-observability ...

designs, ReAct‐style loops, state and checkpointing, retries and interrupts, human‐in‐the‐loop review gates. Frameworks: At least one of: Anthropic Agent SDK, LangGraph, LlamaIndex, or an equivalent orchestration framework, plus the judgement to know when to use none of them. RAG and retrieval: Chunking strategy, embeddings, hybrid ...

practices. Preferred Skills Experience with LLM integration, RAG, AI orchestration, or Agentic AI frameworks. Exposure to AI platforms such as Azure OpenAI, OpenAI, LangChain, LangGraph, or Semantic Kernel. Candidate Profile Strong engineering and problem-solving skills. Product engineering mindset with a focus on quality and scalability. Comfortable working within existing ...

Solid understanding of LLMs, Prompt engineering/tuning, Vector DBs (AstraDB, Pinecone, Weaviate etc), RAG pipelines (LlamaIndex, Haystack) and Agent/Workflow Orchestration (LangChain, LangGraph, CrewAI). Knowledge of SLM Finetuning and Distillation is big advantage. Experience and knowledge of Agentic development platforms and experience building and delivery enterprise agentic ...

Agentic Builder Experience: Direct hands-on experience building, prototyping, or solutioning with frontier LLMs and modern AI tools - including OpenAI, Claude, LangChain/LangGraph, Cursor , or multi-agent orchestration frameworks. Agent Interoperability & Open Standards: Experience with Retrieval-augmented Generation (RAG), prompt engineering, background/conversational agents, voice AI integrations ...