26 to 50 of 193 LangChain Jobs in London

Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI More ❯

identifying and mitigating security vulnerabilities during development. Experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines, working with LLM APIs (AWS Bedrock, OpenAI, Azure OpenAI), and using frameworks like LangChain or LangGraph. Strong knowledge of SDLC principles, CI/CD pipelines, and modern engineering practices. Excellent communication and collaboration skills to partner across engineering, product, and governance teams. Bachelor's More ❯

Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real-world consequences. Growth: Multiple openings from mid-level to Principal; training & leadership More ❯

Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real-world consequences. Growth: Multiple openings from mid-level to Principal; training & leadership More ❯

Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real-world consequences. Growth: Multiple openings from mid-level to Principal; training & leadership More ❯

Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real-world consequences. Growth: Multiple openings from mid-level to Principal; training & leadership More ❯

e.g. databases, software engineering practices, cloud computing - especially AWS) and data science (e.g. machine learning process) Excellent knowledge of Python includingPytorch, Tensorflow andSKLearn as well as initial knowledge of LangChain andRAGAS. Familiarity with CI/CD workflows is required and experience with containerisation and deployment using Docker/Kubernetes will be considered a plus 1+ year experience working in relevant More ❯

using Python, SQL, NoSQL, and big data tools, preferably on AWS or Azure. You have hands-on experience with LLM operations and agentic AI tools such as GPT-5, LangChain, and vector databases. You understand MLOps, including deployment, monitoring, and CI/CD pipelines, and can effectively communicate complex technical concepts to diverse audiences. I want to work for a More ❯

communication, organisation, and problem-solving skills. Passion for innovation and ethical, scalable AI. Nice to Have Experience in digital marketing or web development (PHP, HTML, JS). Familiarity with LangChain , RAGAS , or similar frameworks. More ❯

communication, organisation, and problem-solving skills. Passion for innovation and ethical, scalable AI. Nice to Have Experience in digital marketing or web development (PHP, HTML, JS). Familiarity with LangChain , RAGAS , or similar frameworks. More ❯

deploying machine learning models in a production environment. Strong programming skills and deep expertise in Python. Hands-on experience building with agentic or RAG (Retrieval-Augmented Generation) frameworks like LangChain or LlamaIndex. Familiarity with tools for working with Large Language Models via API or in a local context (e.g. HuggingFace transformers). Practical experience using managed AI services and foundation More ❯

deploying machine learning models in a production environment. Strong programming skills and deep expertise in Python. Hands-on experience building with agentic or RAG (Retrieval-Augmented Generation) frameworks like LangChain or LlamaIndex. Familiarity with tools for working with Large Language Models via API or in a local context (e.g. HuggingFace transformers). Practical experience using managed AI services and foundation More ❯

with data scientists, software engineers, and subject-matter experts to deliver innovative solutions. Essential Skills & Experience Advanced Python programming skills with hands-on experience using NumPy, Pandas, Scikit-learn, Langchain, LlamaIndex , and Azure AI Foundry . Proven experience working with Azure cloud services and Generative AI R&D. Strong understanding of machine learning, data modelling , and natural language processing (NLP More ❯

with FastAPI or Flask Orchestration and automation, for example Airflow or asyncio Developed applications using latest LLMs (Anthropic, META, Google, Mistral etc) Experience with multi agent orchestration frameworks (LangGraph, LangChain, MCP, CrewAI etc) Experience in end2end development and deployment of ML models Experience with financial data APIs or market data feeds Nice to have Azure AI Services or Cognitive Search More ❯

with FastAPI or Flask Orchestration and automation, for example Airflow or asyncio Developed applications using latest LLMs (Anthropic, META, Google, Mistral etc) Experience with multi agent orchestration frameworks (LangGraph, LangChain, MCP, CrewAI etc) Experience in end2end development and deployment of ML models Experience with financial data APIs or market data feeds Nice to have Azure AI Services or Cognitive Search More ❯

with FastAPI or Flask Orchestration and automation, for example Airflow or asyncio Developed applications using latest LLMs (Anthropic, META, Google, Mistral etc) Experience with multi agent orchestration frameworks (LangGraph, LangChain, MCP, CrewAI etc) Experience in end2end development and deployment of ML models Experience with financial data APIs or market data feeds Nice to have Azure AI Services or Cognitive Search More ❯

with FastAPI or Flask Orchestration and automation, for example Airflow or asyncio Developed applications using latest LLMs (Anthropic, META, Google, Mistral etc) Experience with multi agent orchestration frameworks (LangGraph, LangChain, MCP, CrewAI etc) Experience in end2end development and deployment of ML models Experience with financial data APIs or market data feeds Nice to have Azure AI Services or Cognitive Search More ❯

Augmented Generation (RAG), and graph databases Familiarity with multi-agent LLM systems and agentic platforms (e.g., AutoGen, CrewAI), and experience deploying LLM-based applications Experience with tools such as LangChain, LangSmith, or Chainlit Exposure to event-driven architectures, asynchronous processing, and tools like Celery or Kafka Familiarity with CI/CD pipelines, Docker, and DevOps workflows Experience designing or integrating More ❯

and a strong interest in general software engineering principles. You have worked with common python frameworks (Numpy, Pandas...) Demonstrated expertise with agentic AI systems , including orchestration frameworks (LangGraph preferred, LangChain or similar also considered). Strong foundation in classical machine learning and applied modeling techniques , including regression, classification, clustering, and practical experience with models used in econometrics or marketing measurement. More ❯

and a strong interest in general software engineering principles. You have worked with common python frameworks (Numpy, Pandas...) Demonstrated expertise with agentic AI systems , including orchestration frameworks (LangGraph preferred, LangChain or similar also considered). Strong foundation in classical machine learning and applied modeling techniques , including regression, classification, clustering, and practical experience with models used in econometrics or marketing measurement. More ❯

Augmented Generation (RAG), and graph databases Familiarity with multi-agent LLM systems and agentic platforms (e.g., AutoGen, CrewAI), and experience deploying LLM-based applications Experience with tools such as LangChain, LangSmith, or Chainlit Exposure to event-driven architectures, asynchronous processing, and tools like Celery or Kafka Familiarity with CI/CD pipelines, Docker, and DevOps workflows Experience designing or integrating More ❯

projects. Ideal Qualifications (Nice-to-Haves) API Integration: Practical experience integrating with third-party APIs and services within AI workflows. AI Frameworks: Familiarity with AI development frameworks such as LangChain or LangGraph. Vector Databases: Understanding of or experience with vector databases (e.g., Pinecone, Weaviate) for managing embeddings. Cloud Platforms: Familiarity with cloud services for deploying and managing applications (e.g., Google More ❯

projects. Ideal Qualifications (Nice-to-Haves) API Integration: Practical experience integrating with third-party APIs and services within AI workflows. AI Frameworks: Familiarity with AI development frameworks such as LangChain or LangGraph. Vector Databases: Understanding of or experience with vector databases (e.g., Pinecone, Weaviate) for managing embeddings. Cloud Platforms: Familiarity with cloud services for deploying and managing applications (e.g., Google More ❯

projects. Ideal Qualifications (Nice-to-Haves) API Integration: Practical experience integrating with third-party APIs and services within AI workflows. AI Frameworks: Familiarity with AI development frameworks such as LangChain or LangGraph. Vector Databases: Understanding of or experience with vector databases (e.g., Pinecone, Weaviate) for managing embeddings. Cloud Platforms: Familiarity with cloud services for deploying and managing applications (e.g., Google More ❯

projects. Ideal Qualifications (Nice-to-Haves) API Integration: Practical experience integrating with third-party APIs and services within AI workflows. AI Frameworks: Familiarity with AI development frameworks such as LangChain or LangGraph. Vector Databases: Understanding of or experience with vector databases (e.g., Pinecone, Weaviate) for managing embeddings. Cloud Platforms: Familiarity with cloud services for deploying and managing applications (e.g., Google More ❯