1 to 25 of 60 Permanent LangChain Jobs in Central London

skills in Python (preferred), with experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps More ❯

skills in Python (preferred), with experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps More ❯

etc.). Ability to design enterprise-level AI/Gen AI platform/solutions with the client’s existing enterprise stack. Hands-on mastery of core GenAI frameworks (e.g., LangChain, LlamaIndex) and practical experience with Agentic AI frameworks and concepts (e.g., AutoGen, CrewAI, LangGraph). Strong working knowledge and practical deployment experience on at least one major cloud platform (AWS More ❯

skills in Python (preferred), with experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps More ❯

Experience with state-of-the-art LLMs (e.g., GPT series, Llama series, Mistral, Claude), including prompt engineering, fine-tuning, and evaluation. Hands-on experience with core GenAI frameworks (e.g., LangChain, LlamaIndex) and Agentic AI frameworks (e.g., AutoGen, CrewAI, LangGraph). Proficiency in MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Strong working knowledge and practical deployment experience on major More ❯

Data & AI strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). Generative AI features: embeddings, RAG, AI agents. Clean, testable code with modern engineering practices. Align with enterprise architecture and governance. Collaborate with architects and stakeholders. Lifecycle More ❯

Data & AI strategy. Key Responsibilities * End-to-end development of AI/ML solutions. * MLOps practices: CI/CD, model monitoring, retraining. * Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). * Generative AI features: embeddings, RAG, AI agents. * Clean, testable code with modern engineering practices. * Align with enterprise architecture and governance. * Collaborate with architects and stakeholders. * Lifecycle More ❯

measures. About You Deep expertise in Python, machine learning, and data science. Experience building, deploying, and scaling AI models in Azure and/or AWS environments. Skilled in using LangChain, LangGraph, vector databases, and prompt engineering. Understanding of LLM optimisation, including context extension and RAG-based frameworks. Proven ability to collaborate cross-functionally and communicate complex AI concepts to non More ❯

AI is applied in a fast-moving SME environment—balancing hands-on technical work with strategic innovation. Key Responsibilities Design, build, and deploy AI agents using frameworks such as LangChain, CrewAI, or similar. Integrate multi-agent systems into existing software products and business workflows. Collaborate with stakeholders to identify automation opportunities and deliver agentic solutions. Fine-tune and optimize LLMs More ❯

Large Language Models (LLMs), including the design, optimization of NLP systems, frameworks, and tools. Application Development with LLMs: Experience in building scalable applications using LLMs, utilizing frameworks such as LangChain, LlamaIndex, etc and productionizing machine learning and AI models. Language Model Development: Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. Cloud Computing More ❯

and a strong interest in general software engineering principles. You have worked with common python frameworks (Numpy, Pandas...) Demonstrated expertise with agentic AI systems , including orchestration frameworks (LangGraph preferred, LangChain or similar also considered). Strong foundation in classical machine learning and applied modeling techniques , including regression, classification, clustering, and practical experience with models used in econometrics or marketing measurement. More ❯

and a strong interest in general software engineering principles. You have worked with common python frameworks (Numpy, Pandas) Demonstrated expertise with agentic AI systems , including orchestration frameworks (LangGraph preferred, LangChain or similar also considered). Strong foundation in classical machine learning and applied modeling techniques , including regression, classification, clustering, and practical experience with models used in econometrics or marketing measurement. More ❯

We are seeking an experienced AI Engineer to lead the integration and strategic application of artificial intelligence in our innovative financial management platform, tailored for sectors like super yachts and touring bands. This role demands expertise in defining AI strategies More ❯

We are seeking an experienced AI Engineer to lead the integration and strategic application of artificial intelligence in our innovative financial management platform, tailored for sectors like super yachts and touring bands. This role demands expertise in defining AI strategies More ❯

We are seeking an experienced AI Engineer to lead the integration and strategic application of artificial intelligence in our innovative financial management platform, tailored for sectors like super yachts and touring bands. This role demands expertise in defining AI strategies More ❯

Core Responsibilities Design, develop, and deploy autonomous AI agents using frameworks like LangChain or LlamaIndex . Implement agent reasoning, planning, and tool use for executing real-world, multi-step workflows. Integrate memory systems and RAG (Retrieval-Augmented Generation) using vector databases for context management. Ensure agent reliability, safety, and governance by establishing robust guardrails and error handling. Collaborate with product More ❯

/CD, automated ML testing, IaC Influence technical direction and mentor other engineers Work cross-functionally to translate AI strategy into measurable business outcomes What you bring Expert Python — LangChain, Semantic Kernel, PyTorch, TensorFlow Hands-on cloud delivery — Azure/AWS, Terraform, ECS Proven experience building RAG/MCP architectures 5+ years in applied ML or AI engineering roles Send More ❯

media agency, consultancy, or fast-paced business. Strong programming skills in Python, with experience building automation workflows, APIs, and data pipelines. Exposure to AI/ML frameworks (e.g. OpenAI, LangChain, TensorFlow, PyTorch). Solid knowledge of SQL and data warehousing concepts. Demonstrated experience with cloud platforms ( GCP & Azure preferred). Strong understanding of data modelling, transformation, and orchestration (e.g. dbt More ❯

that drive significant innovation and efficiency within our global financial services operations. Core Responsibilities Architect Autonomous Agents: Design and implement robust, goal-driven AI agents using leading frameworks like LangChain, LangGraph, and the Google Agent Development Kit (ADK). Develop and Evaluate RAG Pipelines: Engineer and optimize end-to-end Retrieval-Augmented Generation (RAG) systems, including data ingestion, chunking strategies … using Python and FastAPI to integrate agentic systems into the wider enterprise architecture. Technical Skillset Requirements Core AI & Frameworks: Agentic Frameworks: Expert-level knowledge of agentic frameworks such as LangChain, LangGraph, Google Agent Development Kit (ADK) LLM Expertise: Advanced Prompt Engineering and hands-on experience with model fine-tuning techniques including PEFT and QLoRA. Proven experience with models like Gemini More ❯

the categories AI You will have: Actively used AI in your workflows Deployed AI systems at scale Built real-world systems with LLMs Used agent frameworks, like LangGraph or LangChain, RAG pipelines It would be interesting if you have: Contributed to the AI/ML community (open-source, publications, talks) Experienced optimising AI models through fine-tuning, distillation, or human More ❯

practices. Mindset: Demonstrated commitment to continuous learning and excellent communication skills. Good to have- GCP Data Services: Experience with BigQuery, Spanner, Cloud Composer, or Dataflow. Generative AI: Exposure to LangChain, LangGraph, or similar tools; interest in building agentic solutions. More ❯

practices. Mindset: Demonstrated commitment to continuous learning and excellent communication skills. Good to have- GCP Data Services: Experience with BigQuery, Spanner, Cloud Composer, or Dataflow. Generative AI: Exposure to LangChain, LangGraph, or similar tools; interest in building agentic solutions. More ❯

MSc/PhD or equivalent experience). Hands-on experience building or deploying agentic AI or multi-agent systems. Proficiency in Python and modern AI frameworks (e.g. PyTorch, TensorFlow, LangChain, Hugging Face). Familiarity with LLM fine-tuning, reasoning, or retrieval-augmented generation (RAG). Desirable: Experience with AI orchestration, workflow automation, or public-sector technology projects. Knowledge of frameworks More ❯

and software testing practices. Experience delivering customer-facing products and supporting the full development lifecycle. Excellent communication, stakeholder engagement, and advisory skills. Desirable Experience with Generative AI, LLMs, RAG, LangChain, or Semantic Kernel. Familiarity with Microsoft Power Platform. Front-end experience with React, Angular, Vue.js, Flutter, or Progressive Web Apps. Exposure to edge computing, VR/AR, or robotics. What More ❯

systems and Generative AI. · Deep expertise in enterprise architecture frameworks (e.g., TOGAF, Zachman) and cloud-native architecture (preferably Microsoft Azure). · Understanding LLMs and Python-based agentic frameworks like LangChain or AutoGen. · Strong understanding of data governance, security protocols, and MLOps practices in a cloud environment. · Proven track record of designing and deploying scalable AI solutions that deliver measurable business More ❯