1 to 25 of 145 Remote/Hybrid LangChain Jobs in England

automated evals, 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 ...

real-world impact 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 is preferred.Deep understanding of LLMs, prompt engineering, RAG pipelines, vector databases ...

real-world impact 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 is preferred.Deep understanding of LLMs, prompt engineering, RAG pipelines, vector databases ...

tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow or Google ADK* Hands-on experience with Generative and Agentic AI 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 ...

evaluating prompts for 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 ...

prompts for 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 ...

Data Version Control (DVC). Experience developing LLM or Generative AI applications, including RAG architectures and prompt engineering. Knowledge of LLMOps frameworks such as LangChain, LangGraph, or LangSmith. Experience taking ML models from experimentation into production environments. Strong communication skills with the ability to explain technical concepts to both technical ...

stakeholders.Proven experience leading technical teams and mentoring engineers.DesirableExperience within EdTech, SaaS, or digital consumer products.Knowledge of adaptive learning, recommendation systems, or educational analytics.Experience with LangChain, LlamaIndex, vector databases, and AI orchestration frameworks.Understanding of responsible AI, privacy, and ethical AI development.Passion for improving education through technology.Reference: AMC/DJA/SAIML#dajaApply ...

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/ ...

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) LLMOps/MLOps — model versioning, deployment ...

hands‐on with emerging technologies – exploring what works, what scales, and what’s next: Experimenting with Generative AI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, and APIs from OpenAI and Anthropic. Building retrieval‐augmented generation (RAG) prototypes with vector stores and knowledge graphs. Developing and testing agentic architectures ...

hands-on with emerging technologies – exploring what works, what scales, and what’s next:Experimenting with Generative AI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, and APIs from OpenAI and Anthropic.Building retrieval-augmented generation (RAG) prototypes with vector stores and knowledge graphs.Developing and testing agentic architectures through ...

hands-on with emerging technologies – exploring what works, what scales, and what's next: Experimenting with Generative AI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, and APIs from OpenAI and Anthropic. Building retrieval-augmented generation (RAG) prototypes with vector stores and knowledge graphs. Developing and testing agentic architectures ...

tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow or Google ADK Hands-on experience with Generative and Agentic AI 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 ...

Hands-on experience with GCP Vertex AI or equivalent platforms such as AWS SageMaker or Azure ML; Experience with agent orchestration frameworks such as LangChain, LangGraph, or ADK; Solid understanding of MLOps, including CI/CD, Terraform, experiment tracking, model registry, and monitoring; Experience deploying and operating batch and real ...

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). ...

engineering or applied ML building real-world AI/ML systems; strong Python proficiency and backend development expertiseHands-on experience building GenAI apps with LangChain and LangGraph, including agent design, state/memory management, and graph-based orchestration.Proficiency in ML/NLP and generative models; experience with embeddings, vector stores ...

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, customer ...

multiple teamsStrong 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, customer ...

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) - LLMOps/MLOps - model versioning, deployment ...

still being designed and built.Bonus PointsExperience with any of the following would be highly advantageous:AI gateways and model routingPrompt management platformsAI evaluation frameworksLangGraph, LangChain, LlamaIndex, DSPy, CrewAI or similar orchestration frameworksVector databases and semantic retrievalKnowledge graphs or document understanding systemsBuilding internal AI platforms used by multiple engineering teamsBenefitsWe ...

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 language models ...

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 ...

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 ...

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 ...