16 of 16 Contract LangChain Jobs in the UK

Hands-on experience with LLMs/SLMs, Python, Java, SQL/NoSQL. API development, web scraping, data integration. On-prem AI model deployment, open-source frameworks (e.g. Hugging Face, LangChain). Strong consulting and communication skills. Preferred Knowledge of data structures, algorithms, and solution architecture. Experience with cloud AI platforms (AWS, Azure, GCP). Broad ML knowledge and prior consulting More ❯

LLMs, BERT, RoBERTa, GPT-family). Design and implement scalable data pipelines using Python, spaCy, Pandas, and Hugging Face Transformers. Build or enhance retrieval-augmented generation (RAG) systems using LangChain and vector databases like FAISS, Weaviate, or Pinecone. Package and deploy solutions via Docker, Kubernetes, or Vertex AI/SageMaker. Collaborate with internal MLOps and Data Science teams to ensure More ❯

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

Programming proficiency in Python and/or C# Familiarity with: Responsible AI frameworks (e.g., NIST AI RMF, ISO/IEC 42001) Regulatory standards (EU AI Act, GDPR, FCA guidance) LangChain, AutoGen, Azure AI Search, Form Recognizer, and Language Services Excellent communication and documentation skills Experience working in cross-functional teams across engineering, legal, and risk domains More ❯

Chain-of-Thought, ReAct, Tree-of-Thoughts, and more. Deploy AI/ML pipelines using Azure ML, AWS SageMaker, Vertex AI, or Databricks. Integrate LLMs into production apps using LangChain, LlamaIndex, and RAG architectures. Build APIs and microservices for scalable AI deployment. Use AI-powered dev tools like GitHub Copilot, Cursor, and Codeium to speed up iteration. Apply MLOps/… LLMOps practices with MLflow, Weights & Biases, and Kubeflow. ?? Youll Bring Strong Python skills and experience with LangChain, Transformers, Hugging Face. Solid grasp of LLM behavior, prompt optimization, and data engineering. Familiarity with vector databases (FAISS, Pinecone, ChromaDB). Hands-on with Linux, Bash/Powershell scripting, cloud environments. Creative problem-solver with excellent communication and collaboration skills. Curious, adaptable, and … responsible AI principles. Bachelors or Masters degree in Computer Science, AI/ML or related field. Tech Stack LLMs: GPT-4/5, Claude, Gemini, Mistral, LLaMA, Cohere Frameworks: LangChain, LlamaIndex, Haystack Tools: GitHub Copilot, Cursor, PromptLayer, Weights & Biases Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks Infra: Python, Docker, Kubernetes, SQL, PyTorch More ❯

Studio, Power Automate, Power Apps, and custom connectors 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. Contract: 6 Months Rolling Rate: £695 Via Umbrella Location More ❯

Studio, Power Automate, Power Apps, and custom connectors 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. Contract: 6 Months Rolling Rate: £695 Via Umbrella Location More ❯

on expertise with LangChain. Experience with AI model deployment and optimization strategies. Technical Expertise Required: Proficient in Python Experienced with REACT.js Familiar with Node.js Knowledge of Docker Understanding of LangChain Experience with cloud platforms such as Amazon Web Services (AWS) or Azure Familiarity with LLMs and RAG technologies Candidates will need to show evidence of the above in their CV More ❯

front-end frameworks (e.g. React, Next.js, React Native) and back-end systems (e.g. Node.js, Python). AI integrations: Hands-on experience integrating AI tools and services (e.g. OpenAI, Anthropic, LangChain, Pinecone, speech/video APIs). Prototype mindset: You've built MVPs in fast-moving environments and are comfortable with ambiguity. Cloud/data experience: Familiar with AWS, GCP, or More ❯

No-Code: Ability to leverage low-code and no-code solutions where appropriate to accelerate delivery. Nice to Have Exposure to agentic AI, including experience with LLMs, MCP servers, LangChain, and prompt engineering. To apply, please submit your CV and daily rate expectation by clicking on the relevant links. If successful you will be contacted by one of our consultants More ❯

No-Code: Ability to leverage low-code and no-code solutions where appropriate to accelerate delivery. Nice to Have Exposure to agentic AI, including experience with LLMs, MCP servers, LangChain, and prompt engineering. To apply, please submit your CV and daily rate expectation by clicking on the relevant links. If successful you will be contacted by one of our consultants More ❯

AI Agents Solution Architect - Future Talent (Q2/Q3 opportunities) for leading GSI in the software engineering market AI Solution Architect to design and implement AI-driven agent solutions for the online commerce space. Deep understanding of AI/ML More ❯

practices, and observability tools to ensure reliable, high-performing systems. On the AI side, you have practical experience working with large language models (LLMs), prompt engineering, and frameworks like LangChain, with knowledge of advanced patterns such as Retrieval-Augmented Generation (RAG) and agent-based systems. A strong foundation in Agile SDLC practices is essential, along with familiarity in containerization, DevOps … in building microservices, SaaS solutions, and API-first architectures to enable scalable, interoperable systems. Frameworks & Tools: Backend: Spring Boot (web, data, cloud, security), JUnit 5, Mockito, database integration. AI: LangChain, Retrieval-Augmented Generation (RAG), MCP servers (as consumer and developer), and prompt engineering for LLM optimization. Exposure to popular libraries and frameworks (Apache Commons, Guava, Swagger, TestContainers). Architecture & Platforms … application security and model safety considerations. AI Development: End-to-end development of AI-powered solutions, from concept to production readiness. Practical experience with LLMs and agentic AI, including LangChain integration, RAG pipelines, prompt engineering, and model consumption via APIs. Ability to bridge backend and AI workflows, integrating advanced AI capabilities into scalable enterprise platforms. SDLC & Agile Practices: Familiar with More ❯

practices, and observability tools to ensure reliable, high-performing systems. On the AI side, you have practical experience working with large language models (LLMs), prompt engineering, and frameworks like LangChain, with knowledge of advanced patterns such as Retrieval-Augmented Generation (RAG) and agent-based systems. A strong foundation in Agile SDLC practices is essential, along with familiarity in containerization, DevOps … in building microservices, SaaS solutions, and API-first architectures to enable scalable, interoperable systems. Frameworks & Tools:Backend: Spring Boot (web, data, cloud, security), JUnit 5, Mockito, database integration. AI: LangChain, Retrieval-Augmented Generation (RAG), MCP servers (as consumer and developer), and prompt engineering for LLM optimization. Exposure to popular libraries and frameworks (Apache Commons, Guava, Swagger, TestContainers). Architecture & Platforms … application security and model safety considerations. AI Development: End-to-end development of AI-powered solutions, from concept to production readiness. Practical experience with LLMs and agentic AI, including LangChain integration, RAG pipelines, prompt engineering, and model consumption via APIs. Ability to bridge backend and AI workflows, integrating advanced AI capabilities into scalable enterprise platforms. SDLC & Agile Practices: Familiar with More ❯

practices, and observability tools to ensure reliable, high-performing systems. On the AI side, you have practical experience working with large language models (LLMs), prompt engineering, and frameworks like LangChain, with knowledge of advanced patterns such as Retrieval-Augmented Generation (RAG) and agent-based systems. A strong foundation in Agile SDLC practices is essential, along with familiarity in containerization, DevOps … in building microservices, SaaS solutions, and API-first architectures to enable scalable, interoperable systems. Frameworks & Tools: Backend: Spring Boot (web, data, cloud, security), JUnit 5, Mockito, database integration. AI: LangChain, Retrieval-Augmented Generation (RAG), MCP servers (as consumer and developer), and prompt engineering for LLM optimization. Exposure to popular libraries and frameworks (Apache Commons, Guava, Swagger, TestContainers). Architecture & Platforms … application security and model safety considerations. AI Development: End-to-end development of AI-powered solutions, from concept to production readiness. Practical experience with LLMs and agentic AI, including LangChain integration, RAG pipelines, prompt engineering, and model consumption via APIs. Ability to bridge backend and AI workflows, integrating advanced AI capabilities into scalable enterprise platforms. SDLC & Agile Practices: Familiar with More ❯

Title: AI Engineering Research Assistant Location: London, UK Hybrid (3 days onsite) Duration: Until Dec 2025 (ASAP start) Description: We are seeking an experienced Research Assistant to support ongoing work in the artificial intelligence and machine learning domain . The More ❯