1 to 25 of 84 LangChain Jobs in the South East

compliance considerations in AI, especially within financial services and other regulated industries. Experience Hands-on experience with leading ML frameworks (e.g., PyTorch, TensorFlow) and LLM libraries (e.g., Hugging Face, LangChain/LangGraph, LlamaIndex). Practical experience implementing CI/CD pipelines using tools like GitHub Actions or Jenkins, and managing MLOps and LLMOps with MosiacAI, MLflow, Sagemaker or similar platforms. 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 ❯

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 in one or more business domains such as finance, housing, operations, or customer service. Preferred Extras: Degree in Computer Science, AI, Data Science, or related fields. Experience with LangChain, CrewAI, Autogen, MLOps, CI/CD, and enterprise systems like SAP, Oracle, or Salesforce. How You'll Measure Success Number of intelligent agents deployed and adopted. Significant reduction in manual 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 ❯

architecture reviews. Required Skills & Experience: 5+ years in ML/AI solution development. Recent hands-on experience with Databricks, PySpark, Delta Lake, MLflow . Experience with LLMs (Hugging Face, LangChain, Azure OpenAI) . Strong MLOps, CI/CD, and model monitoring experience. Proficiency in Python, PyTorch/TensorFlow, FastAPI/Flask . Cloud architecture experience: Azure preferred, AWS/GCP More ❯

prototype new techniques in AI orchestration and agentic reasoning What We're Looking For Proven experience with LangGraph (bonus: contributions to the open-source project) Strong background in Python, LangChain, OpenAI APIs, and LLM architectures Familiarity with vector databases, retrieval-augmented generation (RAG), and prompt engineering Understanding of software design principles, version control (Git), and CI/CD practices Creative More ❯

Demonstrable experience delivering AI, LLM, or data-driven applications Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn) and/or TypeScript/JavaScript Familiarity with LLM frameworks (LangChain, LlamaIndex) and vector databases (Pinecone, Weaviate) Understanding of cloud platforms (AWS, Azure, or GCP) and modern development workflows (Git, CI/CD) Excellent problem-solving skills and a proactive, collaborative More ❯

Python and leading AI/ML/NLP libraries (e.g. Hugging Face Transformers, spaCy, NLTK) Hands-on experience with LLMs (GPT, Claude, Llama, Mistral) and GenAI/Agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) Proven track record designing scalable AI architectures (RAG, Graph RAG, multi-agent systems) Experience with vector databases (Pinecone, Weaviate, FAISS) and major cloud platforms (AWS, Azure, GCP 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 ❯

Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move Mission & impact: Work on projects where data-driven decisions have real-world consequences. Growth: Multiple openings from mid-level to Principal; training & leadership More ❯

ensure adoption. Define KPIs that measure impact on speed, quality, and cost of clinical trials. Innovative & Experimentation: Stay ahead of the curve on Gen AI and agentic frameworks (e.g., LangChain, Autogen, CrewAI). Evaluate emerging tools and models for integration into the product stack. Process Optimization and Quality Management: Apply Lean and Six Sigma principles to streamline AI-driven workflows More ❯

deploying machine learning models in a production environment. Strong programming skills and deep expertise in Python. Hands-on experience building with agentic or RAG (Retrieval-Augmented Generation) frameworks like LangChain or LlamaIndex. Familiarity with tools for working with Large Language Models via API or in a local context (e.g. HuggingFace transformers). Practical experience using managed AI services and foundation 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 ❯

with data scientists, software engineers, and subject-matter experts to deliver innovative solutions. Essential Skills & Experience Advanced Python programming skills with hands-on experience using NumPy, Pandas, Scikit-learn, Langchain, LlamaIndex , and Azure AI Foundry . Proven experience working with Azure cloud services and Generative AI R&D. Strong understanding of machine learning, data modelling , and natural language processing (NLP More ❯

currently 3 engineers 10+ by EOY) ️ Tech Stack Frontend: React • Next.js • Tailwind • React Query • Shadcn/ui Backend: Node.js • NestJS • MongoDB • Redis • BullMQ • Microservices • GCP AI/ML: Python • LangChain/LangGraph/LangSmith • Qdrant (vector DB) • Pydantic • FastAPI Integrations: WhatsApp Business API • Email • SMS • Webhooks • WebSockets What We're Looking For Must-Haves: Technical Chops 5+ years software engineering 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 operate as a staffing agency and employment business. More information can be found at attisglobal.com. SEO Keywords for Search Senior AI Engineer, Full-Stack AI, Agentic AI, LangGraph, LangChain, Multi-Agent System, Large Language Models, LLMs, Machine Learning, MLOps, Data Scientist, Artificial Intelligence, AWS, Terraform, Kubernetes, EKS, Docker, Containerisation, Python, Go, Bash, CI/CD, GitHub Actions, Argo CD More ❯

projects. Ideal Qualifications (Nice-to-Haves) API Integration: Practical experience integrating with third-party APIs and services within AI workflows. AI Frameworks: Familiarity with AI development frameworks such as LangChain or LangGraph. Vector Databases: Understanding of or experience with vector databases (e.g., Pinecone, Weaviate) for managing embeddings. Cloud Platforms: Familiarity with cloud services for deploying and managing applications (e.g., Google More ❯

using Python, SQL, NoSQL, and big data tools, preferably on AWS or Azure. You have hands-on experience with LLM operations and agentic AI tools such as GPT-5, LangChain, and vector databases. You understand MLOps, including deployment, monitoring, and CI/CD pipelines, and can effectively communicate complex technical concepts to diverse audiences. I want to work for a 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 ❯

/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 ❯

remote UK-based role. ***Unfortunately we can't consider candidates that require sponsorship*** Compensation: Up to £65,000 + package Key Responsibilities: Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like More ❯