11 of 11 Contract LangChain Jobs in the South East

applications, optimizing performance and scalability. Apply backend/data processing skills to handle structured and unstructured datasets. Stay current with open-source AI/ML frameworks (e.g., Hugging Face, LangChain) and apply them to business needs. Communicate technical concepts clearly to technical and non-technical stakeholders. Essential Skills & Experience Hands-on experience in ML, NLP, and GenAI (LLM/SLM More ❯

desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face Trainer, etc.). Experience with ML tooling (e.g. SageMaker, LangChain/LangSmith, MLflow, Dataiku, DataRobot). Knowledge of embeddings, their applications, and limitations. Hands-on experience in Agile/Lean/XP environments. Excellent communication, problem-solving, and cross-team More ❯

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 ❯

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 ❯

Industry experience within financial services Highly Desirable experience with AI/ML, such as Search Index, Azure Machine Learning Desirable experience in Python for data manipulation, analysis, and ML (Langchain) If this role is of interest to you or you would like to learn more, please apply now! Carbon60, Lorien & SRG - The Impellam Group STEM Portfolio are acting as an 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 Engineer LLM, Python, RAG, Data Analyst SQL, Tableau, R, Python, Gen AI, Machine Learning This is 12 month fixed term contract, hybrid working, office location Weybridge, Surrey The Role: Build and refine LLM/SLM-based Generative AI solutions 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 ❯