1 to 25 of 47 Permanent LangChain Jobs in the UK

experience with GCP Vertex AI model endpoints, pipelines, embeddings, vector search or equivalent cloud-native AI/ML platforms e.g. AWS SageMaker, Azure ML and agent orchestration frameworks e.g. LangChain, LangGraph. ·Solid understanding of MLOps CI/CD, IaC Terraform, experiment tracking, model registry, and monitoring. ·Proven experience deploying and operating ML systems in production batch and real-time. ·Familiarity More ❯

ML engineering role, with a demonstrable track record of building and shipping complex systems. Expert-level proficiency in Python and its core AI/ML libraries (e.g., PyTorch, TensorFlow, LangChain, LlamaIndex), and comfortable transitioning to a 'pilot' role using AI tools to amplify your productivity. Proven experience designing, deploying, and managing scalable AI solutions on at least one major cloud More ❯

Large Language Models (e.g., GPT, Llama, Mistral) and NLP workflows (BERT, topic modelling) for production environments. Agentic & Multi-Agent Systems: Design and orchestrate autonomous agentic workflows (using frameworks like LangChain, AutoGen, or CrewAI) that can reason, plan, and execute tasks across multiple tools. Production Engineering: Work collaboratively with Data Engineers to ensure model deployments are supported by robust data storage More ❯

but an eagerness to learn and the ability to leverage AI tooling to get bootstrapped quickly is a must. Core AI & Machine Learning Python Vertex AI/Hugging Face LangChain/BAML — LLM frameworks Langfuse, LangSmith — Observability Pandas, NumPy, scikit-learn, PyTorch — Data & ML stack Data & Infrastructure BigQuery — Cloud data warehouse PostgreSQL — Application data Pulumi — Infrastructure as Code (TypeScript) Google More ❯

and manipulating LLM in data science projects. can work confidently with at least one common language used for manipulating data (e.g., Python, R) and familiar with LLM libraries (e.g., langchain) has some understanding of generative AI technologies in terms of training and fine-tuning language models and regarding good Prompt Engineering has used machine learning to solve real problems for More ❯

optimization, architectures, and evaluation. Experience with data engineering workflows, including ETL, pipeline design, and feature extraction. Proficiency in Python and libraries such as PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain, and OpenAI/Anthropic APIs. Familiarity with DevOps & tooling (Git, CI/CD, API integration), front-end & visualization (Streamlit, Gradio, React), and cloud environments (AWS/GCP/Azure). More ❯

space. The role The role is building AI applications based on LLM and models such as GPT and BERT You'll make use of Python programming, Pyspark, tensorflow, HuggingFace, LangChain, RAG techniques, interfacing with diverse data sets. Cloud data platforms and a diverse set of tools for AI app deployment. The opportunity Work at the forefront of the industry. It More ❯

senior engineers and cross-functional teams to deliver high-quality AI solutions Essential Skills & Experience 2-6 years of Python development experience Hands-on experience with Generative AI frameworks (LangChain, LlamaIndex, Haystack) and LLM APIs Knowledge of prompt engineering, vector databases (Pinecone, ChromaDB, FAISS), and model fine-tuning Cloud deployment experience with Docker/Kubernetes Understanding of transformer architectures, AI More ❯

senior engineers and cross-functional teams to deliver high-quality AI solutions Essential Skills & Experience 2-6 years of Python development experience Hands-on experience with Generative AI frameworks (LangChain, LlamaIndex, Haystack) and LLM APIs Knowledge of prompt engineering, vector databases (Pinecone, ChromaDB, FAISS), and model fine-tuning Cloud deployment experience with Docker/Kubernetes Understanding of transformer architectures, AI More ❯

AI features or automation products Essential skills: Strong experience with Machine Learning, LLMs, NLP and Data Science Proven track record of building and deploying AI models (Python, TensorFlow, PyTorch, LangChain) Hands-on with cloud platforms (preferably Azure, or AWS, GCP) Good understanding of APIs, microservices, and data pipelines Able to prototype quickly and communicate findings clearly Why this role matters More ❯

decision support in healthcare. What they’re looking for Solid programming skills in Python or JavaScript (Node.js) . A good grasp of RESTful APIs . Experience with Hugging Face, LangChain, PyTorch , or similar AI/ML tools. Familiarity with CI/CD practices. A degree in Computer Science, Informatics , or similar. 3+ years building and optimizing backend systems for high More ❯

ready solutions. You'll work across the stack, contribute to infrastructure, and collaborate with multidisciplinary teams to deliver impactful digital experiences. Key Responsibilities Build GenAI applications using frameworks like LangChain, LangGraph, or CrewAI. Develop microservices using Python (FastAPI) or TypeScript (Express). Create front-end applications with React, TypeScript, and frameworks like Next.js or Vite. Integrate LLMs (e.g., OpenAI, Anthropic More ❯

ready solutions. You'll work across the stack, contribute to infrastructure, and collaborate with multidisciplinary teams to deliver impactful digital experiences. Key Responsibilities Build GenAI applications using frameworks like LangChain, LangGraph, or CrewAI. Develop microservices using Python (FastAPI) or TypeScript (Express). Create front-end applications with React, TypeScript, and frameworks like Next.js or Vite. Integrate LLMs (e.g., OpenAI, Anthropic More ❯

improving search, discoverability, and insight accuracy. LLM & Machine Learning Application Engineering Design, build, and maintain traditional ML and LLM models and pipelines . Build LLM apps using LangGraph/LangChain : tools/function calling, structured outputs (JSON Schema), agents, and multi-step reasoning. Implement ASR/TTS and multimodal where relevant (e.g., Whisper ). Choose customization paths pragmatically: prompt engineering 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 ❯

detection frameworks. Security & Compliance:Knowledge of data privacy, access control, and secure data exchange protocols. Defining and creating MLOPs pipeline Good to Have Skills GenAI Exposure:Experience with LLMs, LangChain, HuggingFace, synthetic data generation, and prompt engineering. Digital Twin Integration:Familiarity with nVidia Omniverse, AWS TwinMaker, Azure Digital Twin or similar platforms and concepts Visualization Tools:Power BI, Grafana, or More ❯

RAG architectures, including vector databases, embedding strategies, and retrieval optimisation Strong experience with evaluation and observability tools for AI systems Familiarity with Agentic frameworks such as OpenAI Agent SDK, LangChain, CrewAI Hands-on experience with AI-assisted software development tools such as Claude Code, GitHub Copilot, Cursor Proficient in Python with experience in relevant ML/AI libraries and frameworks More ❯

Strong foundation in object-oriented design, modular architecture, and reusable software components AI/ML Integration Experience Experience integrating AI/ML APIs and tools (e.g., OpenAI, Hugging Face, LangChain), or a strong interest in learning how to apply AI in real-world tools Exposure to building intelligent features such as generative design aids, semantic search, or context-aware interfaces More ❯

deliver enterprise AI solutions Requirements What We're Looking For Strong skills in Python, APIs, and cloud platforms (AWS, Azure, GCP) Experience with LLMs, prompt engineering, and frameworks like LangChain, AutoGen Knowledge of multi-agent systems, vector databases, and AI orchestration 3+ years in Generative AI or Agentic AI development More ❯

experience. Hands-on work with vector databases, hybrid retrieval methods, and evaluation of retrieval quality. Agentic & Orchestrated Systems – exposure to multi-step reasoning, agent frameworks, or orchestration tools (e.g. LangChain, AutoGen, Inngest, Temporal) where LLMs call tools, plan tasks, or coordinate workflows. Experience working in collaboration with researchers so that new models, pipelines, or research outputs can be integrated and More ❯

Experience on at least one of the 3 major cloud platforms- AWS, Azure, GCP Knowledge of GenAI technologies, including LLMs (Large Language Models), generative models, and related frameworks (e.g., LangChain, TensorFlow, etc.) Possess knowledge of cloud-based AI/ML services like AWS SageMaker, Azure Machine Learning, Google AI Platform, Databricks GenAI/BI, Snowflake GenAI, and their relevant services More ❯

AI/ML. Proven skills in data engineering (ETL pipelines, APIs, SQL/NoSQL, data warehouses like BigQuery/Redshift). Experience with AI agents, LLMs and orchestration frameworks (LangChain, AutoGen, LlamaIndex, etc.). Demonstrated ability to ship production-ready internal tools or SaaS integrations. Strong problem-solver who can translate messy business requirements into clean technical solutions. Excellent collaboration More ❯

have: 1+ year of fullstack experience (open to senior/staff-level engineers too) Production experience with Model Context Protocol (MCP) is highly desired Experience working with LLMs, RAGs, Langchain, OpenAI, Claude etc is beneficial Generative AI Product experience Production-grade Python skills Frontend experience with Vue + TypeScript , or React and a willingness to learn Vue Understanding of web More ❯

using IDE integrations with AI agents Coding with LLMs, e.g. setting up Cursor/Copilot configs, and writing prompts for coding/debugging Integrating/Pipelining with LLMs, e.g. langchain Customising LLM tools, e.g. fine tuning LLMs, using RAG systems You'll need to have significant expertise and experience in a real-world setting, be able to give nuanced answers More ❯

production. Strong understanding of model selection, fine-tuning, prompt engineering, and evaluation methods. Python, SQL, dbt, Airflow Understand how to frame prompts, evaluate outputs of LLMs, manage prompts with LangChain Platforms: Snowflake Cortex, AWS Bedrock Evaluate costs/performance advantages of models on Bedrock vs Snowflake, the size of the model, fine-tune smaller models Create logic for summarising calls More ❯