1 to 25 of 82 LangChain Jobs in London

Claude Code, Codex, and GitHub Copilot for technical analysis, code generation and code review. Hands-on experience with AI/ML frameworks (PyTorch, TensorFlow, HuggingFace) and LLM orchestration tools (LangChain, LangGraph, or similar) Experience deploying ML models using containerised solutions (Docker, Kubernetes) and frameworks like BentoML or equivalent. Familiarity with vector databases and retrieval pipelines for RAG architectures. Knowledge of More ❯

Language Models (fine tuning, RAG, agents) Experience with graph technology and/or algorithms Our technology stack Python and associated ML/DS libraries (scikit-learn, numpy, LightlGBM, Pandas, LangChain/LangGraph TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow More information: Enjoy fantastic perks like private healthcare & dental insurance, a generous work More ❯

Qualifications Skills & Expertise Strong experience in machine learning, deep learning, and statistical analysis. Expertise in Python, with proficiency in ML and NLP libraries such as Scikit-learn, TensorFlow, Faiss, LangChain, Transformers and PyTorch. Experience with big data tools such as Hadoop, Spark, and Hive. Familiarity with CI/CD and MLOps frameworks for building end-to-end ML pipelines. Proven More ❯

ReAct for building more effective autonomous agents for complex property management workflows and decision-making processes Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch), LLM orchestration tools (LangChain, LangGraph), MLOps practices and tooling (such as MLflow, Kubeflow, or similar), vector databases, and cloud platforms (AWS, Azure, GCP) with their AI/ML offerings Preferably hands-on experience with More ❯

control (Git) Experience working in cloud environments (AWS, GCP, or Azure) Ability to work independently and communicate effectively in a remote team Bonus Points Experience with Hugging Face Transformers , LangChain , or RAG pipelines Knowledge of MLOps tools (e.g. MLflow, Weights & Biases, Docker, Kubernetes) Exposure to data engineering or DevOps practices Contributions to open-source AI projects or research publications What More ❯

libraries. Hands-on experience with cloud technologies and services (e.g., AWS, Azure, Google Cloud) Experience with SQL and/or Snowflake. Some experience with Generative AI technologies (e.g. Bedrock, Langchain, LangGraph). Terms like RAG and Graphs are nothing new for you. Proficiency in data preprocessing and feature and/or prompt engineering. Customer-focused engineer with a passion for More ❯

priorities and influence the product roadmap What we look for: Experience building Generative AI applications, including RAG, agents, text2sql, fine-tuning, and deploying LLMs, with tools such as HuggingFace, Langchain, and OpenAI Extensive hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch Experience building production-grade machine More ❯

priorities and influence the product roadmap What we look for: Experience building Generative AI applications, including RAG, agents, text2sql, fine-tuning, and deploying LLMs, with tools such as HuggingFace, Langchain, and OpenAI Extensive hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch Experience building production-grade machine More ❯

learning techniques and GenAI concepts such as prompt engineering, chain-of-thought reasoning, prompt chaining, Retrieval-Augmented Generation (RAG), custom-built agents. Familiarity with LLM and agentic frameworks like LangChain, PydanticAI, or similar. Proficiency in ML-Ops practices and tools; strong understanding of DevOps and CI/CD. Experience with cloud platforms, e.g. AWS (preferred), GCP, and deploying models in More ❯

of design/implementation of production AI/ML systems and MLOps pipelines with hands-on experience with state-of-the-art data and ML frameworks (PyTorch, HuggingFace, Spark, Langchain), technical familiarity with LLMs/FMs, RAG, and prompt engineering techniques. PREFERRED QUALIFICATIONS - History of successful technical consulting and/or architecture engagements with large-scale customers or enterprises. - Experience More ❯

of Docker , CI/CD workflows, and automation pipelines Familiarity with MLOps tooling such as MLFlow, Git version control, and environment management Desirable Skills & Interests: Experience with frameworks like LangChain , Langflow , or similar tools for building AI agents Understanding of Large Language Models (LLMs) and intelligent automation workflows Experience building high-availability, scalable systems using microservices or event-driven architecture More ❯

partners to match value proposition to business needs. Thrived as a another fast-paced SaaS startup or scale-up during a high-growth phase. Preferred to have: expertise with langchain and similar tools for multimodal AI projects. What's in it for you: £80-100k base salary with £25k additional commission Top 15% quartile equity options plan through an More ❯

Have good communication skills. Nice to have Experience deploying LLMs and agent-based systems Our technology stack Python and associated ML/DS libraries (scikit-learn, numpy, pandas, LightGBM, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, ECR, Athena, etc. MLOps: Terraform, Docker, Spacelift, Airflow, MLFlow Monitoring: New Relic CI/CD: Jenkins, Github Actions More information More ❯

pipelines, and observability tools. Hands-on experience with languages and tools like Ruby, Java, React, GraphQL, AWS/GCP, and Kubernetes. Bonus: Experience with vector databases, LLM frameworks (e.g., LangChain, RAG), and open-source AI tools. Excellent communication, collaboration, and problem-solving skills. Strong organizational skills with a passion for continuous improvement. Agile Practices: Demonstrated success with agile product development More ❯

to use them. Familiarity with trunk-based development in Git. Experience with back-end web application frameworks (Django, FastAPI, etc.). Experience with language models and agentic workflows (e.g., Langchain, AutoGPT). Knowledge of model evaluation metrics and techniques. Google Cloud (Cloud Functions, AppEngine, PubSub, Stackdriver, etc.). Docker, Kubernetes. Typescript, NodeJS, React, Webpack, etc. Java, C#. Experience within the More ❯

be nice if you have: Exposure to container orchestration (e.g., Kubernetes) Experience building or maintaining infrastructure for AI workloads, including support for agents, LLMs, or vector databases. Familiarity with LangChain, LangSmith, or similar agent orchestration and tracing tools. Experience managing and scaling applications in cloud environments, particularly with Azure. As part of our commitment to information security, all employees are More ❯

community. Engineering Design, develop, and optimize AI/ML features in Qdrant's core engine and SDKs. Prototype and implement integrations with popular ML frameworks (e.g., Hugging Face, OpenAI, LangChain). Analyze performance, identify bottlenecks, and implement scalable solutions in real-world AI pipelines. Collaborate with product and engineering teams to define and deliver impactful features. Community & Customer Engagement Support More ❯

products, or business applications. Full-stack development experience with AI technologies/tools and apply it to user experiences or backend solutions. Experience with AI technologies like SageMaker, Vert.x, LangChain, Large Language Models, Prompt Engineering, DialogFlow, Python Experience with at least one of the following: Front-end technologies like React, Angular, SwiftUI (iOS), Kotlin (Android) Back-end technologies like Java More ❯

/Flask for Python backend services, with additional OfficeJS API knowledge preferred Extensive knowledge of AI and machine learning ecosystems, including proficiency in modern RAG/Agent frameworks including Langchain/Langgraph, Llamaindex, Pydantic, Vercel AI SDK, and DSPY Strong analytical and problem-solving skills, with the ability to translate complex business requirements into effective AI solutions. Excellent collaboration and More ❯

technical requirements and solution architecture for complex AI systems. Strong experience building and consuming API services in Python, using FastAPI or similar. Strong experience with LLM frameworks such as langchain, Pydantic-AI, Google ADK, OpenAI's Assistants, litellm, etc (it's not required to know them all), and an understanding of how they facilitate agentic AI development. Strong practical knowledge More ❯

be nice if you have: Exposure to container orchestration (e.g., Kubernetes) Experience building or maintaining infrastructure for AI workloads, including support for agents, LLMs, or vector databases. Familiarity with LangChain, LangSmith, or similar agent orchestration and tracing tools. Experience managing and scaling applications in cloud environments, particularly with Azure. As part of our commitment to information security, all employees are More ❯

compliance teams to deliver real-world results What We’re Looking For • 5+ years' ML experience with strong Python skills • Experience with NLP, LLMs, and prompt engineering • Familiarity with LangChain, Semantic Kernel, or AutoGen • OCR/document layout modelling experience • Cloud-native deployment experience (AWS, Azure, or GCP) • Strong engineering mindset – writing production-grade, scalable code Bonus Points For • Experience More ❯

compliance teams to deliver real-world results What We're Looking For • 5+ years' ML experience with strong Python skills • Experience with NLP, LLMs, and prompt engineering • Familiarity with LangChain, Semantic Kernel, or AutoGen • OCR/document layout modelling experience • Cloud-native deployment experience (AWS, Azure, or GCP) • Strong engineering mindset - writing production-grade, scalable code Bonus Points For • Experience More ❯

Terraform. Minimum Requirements · 5+ years of experience as a Software Engineer, with at least 2 years in AI/ML or LLM-centric development. · Proven track record with LangGraph, LangChain, or similar orchestration frameworks. · Expert in Python (asyncio, FastAPI preferred). · Hands-on experience building and deploying applications on AWS, particularly using Lambda, Fargate, S3, Step Functions, and DynamoDB. · Familiarity More ❯

Automate, Power Apps, and custom connectors SharePoint Development Proficiency in Microsoft Graph API, Azure OpenAI, and Semantic Kernel Solid programming skills in Python and/or C# Experience with: LangChain, AutoGen, or similar orchestration frameworks Azure AI Search, Form Recognizer, and Language Services GitHub Actions, CI/CD, and DevSecOps practices Familiarity with: Responsible AI frameworks (e.g., NIST AI RMF More ❯