1 to 25 of 28 LangChain Jobs in the South East

experience with GCP Vertex AI model endpoints, pipelines, embeddings, vector search or equivalent cloud-native AI/ML platforms e.g. AWS SageMaker, Azure ML and agent orchestration frameworks e.g. LangChain, LangGraph. ·Solid understanding of MLOps CI/CD, IaC Terraform, experiment tracking, model registry, and monitoring. ·Proven experience deploying and operating ML systems in production batch and real-time. ·Familiarity More ❯

ML engineering role, with a demonstrable track record of building and shipping complex systems. Expert-level proficiency in Python and its core AI/ML libraries (e.g., PyTorch, TensorFlow, LangChain, LlamaIndex), and comfortable transitioning to a 'pilot' role using AI tools to amplify your productivity. Proven experience designing, deploying, and managing scalable AI solutions on at least one major cloud More ❯

Large Language Models (e.g., GPT, Llama, Mistral) and NLP workflows (BERT, topic modelling) for production environments. Agentic & Multi-Agent Systems: Design and orchestrate autonomous agentic workflows (using frameworks like LangChain, AutoGen, or CrewAI) that can reason, plan, and execute tasks across multiple tools. Production Engineering: Work collaboratively with Data Engineers to ensure model deployments are supported by robust data storage More ❯

but an eagerness to learn and the ability to leverage AI tooling to get bootstrapped quickly is a must. Core AI & Machine Learning Python Vertex AI/Hugging Face LangChain/BAML — LLM frameworks Langfuse, LangSmith — Observability Pandas, NumPy, scikit-learn, PyTorch — Data & ML stack Data & Infrastructure BigQuery — Cloud data warehouse PostgreSQL — Application data Pulumi — Infrastructure as Code (TypeScript) Google More ❯

and manipulating LLM in data science projects. can work confidently with at least one common language used for manipulating data (e.g., Python, R) and familiar with LLM libraries (e.g., langchain) has some understanding of generative AI technologies in terms of training and fine-tuning language models and regarding good Prompt Engineering has used machine learning to solve real problems for More ❯

optimization, architectures, and evaluation. Experience with data engineering workflows, including ETL, pipeline design, and feature extraction. Proficiency in Python and libraries such as PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain, and OpenAI/Anthropic APIs. Familiarity with DevOps & tooling (Git, CI/CD, API integration), front-end & visualization (Streamlit, Gradio, React), and cloud environments (AWS/GCP/Azure). More ❯

senior engineers and cross-functional teams to deliver high-quality AI solutions Essential Skills & Experience 2-6 years of Python development experience Hands-on experience with Generative AI frameworks (LangChain, LlamaIndex, Haystack) and LLM APIs Knowledge of prompt engineering, vector databases (Pinecone, ChromaDB, FAISS), and model fine-tuning Cloud deployment experience with Docker/Kubernetes Understanding of transformer architectures, AI More ❯

ready solutions. You'll work across the stack, contribute to infrastructure, and collaborate with multidisciplinary teams to deliver impactful digital experiences. Key Responsibilities Build GenAI applications using frameworks like LangChain, LangGraph, or CrewAI. Develop microservices using Python (FastAPI) or TypeScript (Express). Create front-end applications with React, TypeScript, and frameworks like Next.js or Vite. Integrate LLMs (e.g., OpenAI, Anthropic More ❯

improving search, discoverability, and insight accuracy. LLM & Machine Learning Application Engineering Design, build, and maintain traditional ML and LLM models and pipelines . Build LLM apps using LangGraph/LangChain : tools/function calling, structured outputs (JSON Schema), agents, and multi-step reasoning. Implement ASR/TTS and multimodal where relevant (e.g., Whisper ). Choose customization paths pragmatically: prompt engineering More ❯

communication, organisation, and problem-solving skills. Passion for innovation and ethical, scalable AI. Nice to Have Experience in digital marketing or web development (PHP, HTML, JS). Familiarity with LangChain , RAGAS , or similar frameworks. More ❯

RAG architectures, including vector databases, embedding strategies, and retrieval optimisation Strong experience with evaluation and observability tools for AI systems Familiarity with Agentic frameworks such as OpenAI Agent SDK, LangChain, CrewAI Hands-on experience with AI-assisted software development tools such as Claude Code, GitHub Copilot, Cursor Proficient in Python with experience in relevant ML/AI libraries and frameworks More ❯

Strong foundation in object-oriented design, modular architecture, and reusable software components AI/ML Integration Experience Experience integrating AI/ML APIs and tools (e.g., OpenAI, Hugging Face, LangChain), or a strong interest in learning how to apply AI in real-world tools Exposure to building intelligent features such as generative design aids, semantic search, or context-aware interfaces More ❯

deliver enterprise AI solutions Requirements What We're Looking For Strong skills in Python, APIs, and cloud platforms (AWS, Azure, GCP) Experience with LLMs, prompt engineering, and frameworks like LangChain, AutoGen Knowledge of multi-agent systems, vector databases, and AI orchestration 3+ years in Generative AI or Agentic AI development More ❯

experience. Hands-on work with vector databases, hybrid retrieval methods, and evaluation of retrieval quality. Agentic & Orchestrated Systems – exposure to multi-step reasoning, agent frameworks, or orchestration tools (e.g. LangChain, AutoGen, Inngest, Temporal) where LLMs call tools, plan tasks, or coordinate workflows. Experience working in collaboration with researchers so that new models, pipelines, or research outputs can be integrated and More ❯

Cloud Run and Kubernetes (GKE) . Familiarity with GCP data tools like BigQuery and Google Cloud Storage (GCS) . Experience building complex agentic AI applications (beyond basic RAG or LangChain implementations). How We Evaluate Candidates Our interview process is designed to identify practical engineering competence and collaborative skills. Technical Acumen: The technical assessment is rigorous. We evaluate Python and More ❯

AI/ML. Proven skills in data engineering (ETL pipelines, APIs, SQL/NoSQL, data warehouses like BigQuery/Redshift). Experience with AI agents, LLMs and orchestration frameworks (LangChain, AutoGen, LlamaIndex, etc.). Demonstrated ability to ship production-ready internal tools or SaaS integrations. Strong problem-solver who can translate messy business requirements into clean technical solutions. Excellent collaboration More ❯

data. Collaborate with data scientists and engineers to deploy scalable AI solutions. Required Skills Strong experience with GraphRAG or Graph-based RAG architectures. Proficiency in Python and frameworks like LangChain, Semantic Kernel, or similar. Hands-on with graph databases (Neo4j, TigerGraph) and vector DBs (Pinecone, Weaviate, FAISS). Knowledge of LLMs, prompt engineering, and retrieval optimization. Familiarity with knowledge graph More ❯

where this was necessary. You either have professional experience using LLMs or have enthusiastically experimented in your own time. Industry experience with LLM toolchains and ecosystems (e.g. libraries like Langchain, observability tooling, RAG systems, etc.) is a plus. You have a fundamental understanding of code analysis, compilers, domain-specific languages, or related topics, and are keen to learn in this More ❯

data, improving search, discoverability, and insight accuracy. LLM & Machine Learning Application Engineering Design, build, and maintain traditional ML and LLM models and pipelines. Build LLM apps using LangGraph/LangChain: tools/function calling, structured outputs (JSON Schema), agents, and multi-step reasoning. Implement ASR/TTS and multimodal where relevant (e.g., Whisper). Choose customization paths pragmatically: prompt engineering … and relevant ML/LLM libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn). Strong in Python, API design, asynchronous programming, and integration patterns. Hands-on with LangGraph/LangChain, LlamaIndex or Semantic Kernel for orchestration (tools, agents, guards, structured I/O). Familiarity with Azure OpenAI and at least one open model stack (e.g., Llama/Mistral via More ❯

with Infrastructure as Code tools (e.g., Terraform). Understanding of accessibility standards and web development best practices. Bonus: Experience with C#, GOV.UK Design System, or integrating with LLMs (e.g., LangChain, Vercel AI). What You'll Gain Exposure to high-impact digital transformation projects. Access to training and certifications in cloud, DevOps, cybersecurity, and agile delivery. Opportunities to work with More ❯

so we're looking for someone who can get stuck in and help us move fast. Tech Stack: , AWS API Gateway/EKS/Step Functions, React, TypeScript, Langgraph, Langchain, gpt-oss, AWS. What You'll Do Build and scale backend services in JavaScript to improve the core functionality of our AI voice tutor. Work hands-on with large language More ❯

to-end with Next.js for a unified development experience. AWS and Terraform for scalable, version-controlled infrastructure. TurboRepo for rapid code sharing and efficient testing. AI-driven architecture using LangChain and custom orchestration for real-world solutions. What's on Offer Permanent role with a competitive salary and meaningful equity . Brand-new MacBook and full setup provided. Private medical More ❯

for an AI Engineer to join a scaling startup in the Education sector Salary up to £70k , depending on experience Fully remote role (Europe-based) Tech stack: Python, LLMs, LangChain, AI Agents, SQL, GCP, ML If you wish to keep your CV/data private, feel free to WhatsApp your details/CV to me, Dan - WHO WE ARE: We … BE DOING: Design and develop AI-driven systems and tools that enhance the learning experience for students and educators. Build and deploy LLM-based solutions, integrating frameworks such as LangChain, AutoGen, and RAG pipelines. Develop and optimise AI agents capable of reasoning, planning, and automating complex learning or data workflows. Collaborate with cross-functional teams to integrate AI components into … with data engineers and product teams to ensure AI models are reliable, efficient, and explainable. AI ENGINEER - ESSENTIAL SKILLS: Proven experience working with LLMs and agentic AI frameworks (e.g. LangChain, AutoGen, CrewAI, RAG). Strong proficiency in Python for AI development, data processing, and API integration. Solid understanding of AI system design, prompt engineering, and model fine-tuning. Experience working More ❯

a MSc or equivalent experience) Hands-on experience building and deploying Agentic AI or multi-agent systems Proficiency in Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong analytical and problem-solving skills … for at least the next 5 years. Profile 29 recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain Hugging Face LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops memory systems governance frameworks public-sector More ❯

a MSc or equivalent experience) Hands-on experience building and deploying Agentic AI or multi-agent systems Proficiency in Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong analytical and problem-solving skills … for at least the next 5 years. Profile 29 recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain Hugging Face LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops memory systems governance frameworks public-sector More ❯