4 of 4 Remote LangChain Jobs in the City of London

language models. You’ll work on fine-tuning, integrating, and scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested More ❯

Microsoft Fabric * Cloud, preferably Azure (Data Lake, Functions, App Services) * Containerisation with Docker and CI/CD pipelines * MLOps tooling (MLFlow, Git-based versioning, environment tracking) Desirable Skills & Interests * LangChain, Langflow, or similar frameworks for building AI agents * LLMs or intelligent automation workflows * High-availability, scalable systems (microservices, event- based architectures) * Orchestration tools like Airflow, container orchestration (Kubernetes), or serverless More ❯

advanced AML/CTF transaction monitoring modules using both traditional statistical methods and modern ML techniques. Develop and deploy machine learning monitors using tools such as TensorFlow, OpenAI APIs, LangChain, Pytest, gRPC, and Python. Assist in implementing generative AI summarisation pipelines and agent communication protocols within a multi-agent system. Drive Deployment and ML Operations: Collaborate with DevOps to containerise … platforms (preferably Azure). Experience with ML frameworks such as TensorFlow or PyTorch. Understanding of ML lifecycles, including model training, validation, testing, and deployment. Exposure to tools such as LangChain, OpenAI, Alembic, and orchestration with Poetry and Mypy is a plus. It’s A Bonus If You Have: Experience working with Generative AI, multi-agent systems, or compliance/regulatory More ❯

deep technical problem-solving. Key Responsibilities: Rapidly design and develop LLM and agent-based prototypes across varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design … with their teams, Google Premier Cloud Partner experience etc Expert Python developer with a background in building intelligent, multi-step systems. Hands-on experience with LLM frameworks such as LangChain, LangGraph, LangFlow, CrewAI, or Autogen. Proven track record designing and deploying agentic and generative AI prototypes. Deep understanding of semantic search, vector databases, and memory management strategies. Familiarity with cloud More ❯