51 to 75 of 163 LangChain Jobs in the UK

years of experience developing AI/ML applications and data-driven solutions ✔️ Strong Python skills with experience using libraries such as Pandas, Scikit-learn, LangChain, and related tools ✔️ Experience working with Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) ✔️ Strong understanding of modern AI techniques including Generative ...

systems and real-world applications. Key skills and experience include: Strong Python development experience Hands-on experience with LLMs and agent frameworks (e.g. LangChain, LlamaIndex, AutoGen or similar) Understanding of prompt engineering, RAG pipelines, and tool-using AI systems Experience working with APIs, data pipelines, and cloud platforms (AWS, Azure ...

enabled environments ·Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns ·Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies ·Understanding of MLOps, LLMOps and model lifecycle management principles ·Experience designing APIs and integrating AI solutions into enterprise environments ·Strong understanding of modern ...

enabled environments ·Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns ·Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies ·Understanding of MLOps, LLMOps and model lifecycle management principles ·Experience designing APIs and integrating AI solutions into enterprise environments ·Strong understanding of modern ...

enabled environments ·Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns ·Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies ·Understanding of MLOps, LLMOps and model lifecycle management principles ·Experience designing APIs and integrating AI solutions into enterprise environments ·Strong understanding of modern ...

direction. Background: Experience in the banking or financial industry is beneficial. Beneficial Skills: Experience with Vertex AI or other model lifecycle tooling. Knowledge of LangChain/LangGraph, RAG patterns, and AI workflow orchestration. Experience in multi cloud (GCP/Azure/AWS) or hybrid environments. Understanding of enterprise integration ...

experience developing AI/ML applications and data-driven solutions • Excellent knowledge of Python and core data science libraries such as pandas, scikit-learn, LangChain, etc. • Experience with LLMs, including foundation model APIs, prompt engineering, and retrieval augmented generation • Substantial depth and breadth across state-of-the-art AI/ ...

lifecycle best practices Hands-on experience with ML libraries: PyTorch, PySpark, scikit-learn, Hugging Face Transformers Proficiency in AI tooling: Azure ML, Databricks, MLflow, LangChain, LangGraph Proven experience with Git, unit testing, containerisation and agile methodologies (Jira, Confluence) Good knowledge of generative AI, machine learning, deep learning or NLP Strong ...

Excellent stakeholder management and communication skills Desirables Hands-on exposure to AI engineering concepts such as Python, prompt engineering, or agent frameworks Experience with LangChain, LangGraph, LlamaIndex, or similar AI tooling Knowledge of Claude (Anthropic), AI APIs, or agentic workflows Experience working within financial services, reporting, environmental or regulatory environments ...

Scientist: Experience with the latest techniques in natural language processing, including vector databases, fine‐tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI. Hands‐on experience working with Distributed Spark based systems. Experience communicating and teaching technical concepts to non‐technical and technical audiences alike. Passion ...

Scientist: Experience with the latest techniques in natural language processing, including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI Hands-on experience working with Distributed Spark based systems. Experience communicating and teaching technical concepts to non-technical and technical audiences alike. Passion ...

Scientist: Experience with the latest techniques in natural language processing, including vector databases, fine‐tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI. Hands‐on experience working with Distributed Spark based systems. Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc. ...

reinforcement learning techniques for model alignment (RLHF, RLAIF, DPO, PPO) and safety/red‐teaming methodologies Deep familiarity with advanced agentic frameworks and architectures (LangChain, LangGraph, DSPy, AutoGen, or equivalent), including multi‐agent orchestration and tool use Experience with multimodal AI systems (text, image, code, speech) and cross‐modal reasoning ...

software or systems architecture, with strong focus in AI/ML domains. Proven experience designing and deploying AI solutions using frameworks such as LangChain, RAG, and vector databases or the MCP protocol. Deep understanding of LLMs, prompt engineering, model evaluation, and fine‐tuning strategies. Strong proficiency in ML frameworks (e.g. ...

years experience in Data Science/ML or related roles • Data Science beyond analytics - building pipelines, along with strong Python and software engineering principles • LangChain/LangGraph/agentic AI experience is a must • FastAPI, MCP/FastMCP, tool-calling or agent tooling • RAG, LLMs, prompt engineering and evaluation • Ability ...

experience developing AI/ML applications and data driven solutions Excellent knowledge of Python and core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ ...

experience developing AI/ML applications and data driven solutions Excellent knowledge of Python and core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ ...

experience developing AI/ML applications and data driven solutions Excellent knowledge of Python and core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ ...

experience developing AI/ML applications and data driven solutions Excellent knowledge of Python and core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ ...

experience developing AI/ML applications and data driven solutions Excellent knowledge of Python and core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ ...

experience developing AI/ML applications and data driven solutions Excellent knowledge of Python and core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ ...

Familiarity with LLM evaluation strategies and how to measure whether your system is actually working Hands-on with AI orchestration frameworks: LangGraph, LangChain, DSPy or equivalent Knowledge of model optimisation for production deployment (quantisation, distillation, fine-tuning approaches) is a strong plus for at least one of these roles Attributes ...

should have strong Python development skills •Solid understanding of machine learning fundamentals and AI concepts •Experience with frameworks such as PyTorch, TensorFlow or LangChain •Experience developing and deploying machine learning models into production •Knowledge of data pipelines and CI/CD practices •Experience with Docker, Kubernetes or similar technologies •Familiarity ...

etc.) Hands-on experience with LLM-based applications Experience building RAG systems and agentic workflows that leverage external tools. Familiarity with agentic SDKs (ADK, LangChain, LlamaIndex, etc.) Proven track record of deploying AI applications into production environments Strong understanding of API development, microservices, and containerization (Docker, Kubernetes) Knowledge of MLOps ...

with a track record of incremental, agile delivery. Hands‐on development capability, including practical experience with Python and modern AI frameworks (e.g., LangChain, Semantic Kernel, or similar) to build or support agents, chat interfaces, or retrieval‐augmented solutions. Experience applying software engineering fundamentals: writing tests, structuring user stories, managing iterative ...