276 to 300 of 306 Permanent LangChain Jobs

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 ❯

AI Technical Consultant Location: Weybridge, Surrey Remuneration: £60,000 - £70,000 depending on experience Join a pioneering team dedicated to innovative artificial intelligence solutions! We are looking for an AI Technical Consultant to enhance and drive smart, strategic integrations of More ❯

features in a regulated environment with sensitive data. You’ll work with engineering to move models from idea to production. Tech Stack: Python, scikit-learn, PyTorch, TensorFlow/Keras, LangChain, Pydantic, Spark, Kafka, Databricks, MLflow, Azure, Docker, Kubernetes. Salary: Up to £100k Working Environment: Fully Remote in UK What you’ll do Research, prototype, and deploy LLM use cases (Q … and Kafka Use Databricks and MLflow for experiments, deployment, and monitoring What you’ll bring Hands-on Python for data science and ML Practical experience with LLM frameworks (e.g. LangChain) Familiar with Spark/Kafka and End-to-end pipeline experience Databricks, MLflow, Docker, Kubernetes Clear communication with technical and non-technical stakeholders If you are interested apply below or More ❯

office. Duration; long term Position type: W2 contract. Mandatory skills: AI/ML architecture, ML and Generative AI (GenAI) use cases, Large Language Models (LLMs), RAG (Retrieval-Augmented Generation), LangChain, LangGraph,CI/CD for AI pipelines Min experience: 10+ Years Job Description: Define and drive the AI/ML architecture and roadmap, including traditional ML and Generative AI (GenAI … data ingestion, feature engineering, model training, inference pipelines, and monitoring frameworks. Lead the integration of Large Language Models (LLMs) and RAG (Retrieval-Augmented Generation) frameworks using tools such as LangChain, LangGraph, or similar. Collaborate with stakeholders to translate business requirements into AI-driven technical solutions. Evaluate and select appropriate AI/ML tools, cloud services, frameworks, and libraries for specific More ❯

Python/GenAI Engineer - LangChain, LangGraph, LLM, Langsmith, Langfuse My client (well known consultancy) brings together strategy, design, data science, and engineering to deliver transformative solutions. If you're passionate about GenAI, development, and shaping the digital future, this role is for you. This fantastic company offers excellent training to all their consultants, both online and classroom training. Candidates can … on engineer with experience and a passion for GenAI. Must Have: Strong Engineering skills in Python - 2yrs commercial minimum Any front-End experience is advantageous Experience with GenAI tools (LangChain, LangGraph, etc.) and LLMs (OpenAI, Anthropic, Llama, etc.) Familiarity with monitoring (Langsmith, Langfuse), Git, and vector/NoSQL/SQL databases Eligible for SC Clearance - lived in the UK for More ❯

Artifical Intelligence (AI) Engineer Central London - Twice a week in the office £80,000-£100,000 I’m currently working with a well-established London FinTech SaaS business, who are looking for a AI Engineer to join their growing team More ❯

Artifical Intelligence (AI) Engineer Central London - Twice a week in the office £80,000-£100,000 I’m currently working with a well-established London FinTech SaaS business, who are looking for a AI Engineer to join their growing team More ❯

Artifical Intelligence (AI) Engineer Central London - Twice a week in the office £80,000-£100,000 I’m currently working with a well-established London FinTech SaaS business, who are looking for a AI Engineer to join their growing team More ❯

Build and deploy AI/ML systems that boost accuracy, speed, and user experience. Partner with domain experts to turn complex workflows into AI-driven automation . Leverage LLMs, LangChain, and RAG at scale. Ship quickly, iterate fast, and set the foundation for our engineering culture . Requirements 2+ years in AI/ML engineering or applied research. Proven track … from idea → production with measurable impact. Deep hands-on expertise with LLMs (fine-tuning, prompt engineering, evaluation, and deployment at scale). Hands-on experience with PyTorch/TensorFlow, LangChain, vector databases , or similar tools. Excellent communicator; comfortable working with non-technical stakeholders. Thrive in chaos and love building zero-to-one . This isn’t just another job - it More ❯

Build and deploy AI/ML systems that boost accuracy, speed, and user experience. Partner with domain experts to turn complex workflows into AI-driven automation . Leverage LLMs, LangChain, and RAG at scale. Ship quickly, iterate fast, and set the foundation for our engineering culture . Requirements 2+ years in AI/ML engineering or applied research. Proven track … from idea → production with measurable impact. Deep hands-on expertise with LLMs (fine-tuning, prompt engineering, evaluation, and deployment at scale). Hands-on experience with PyTorch/TensorFlow, LangChain, vector databases , or similar tools. Excellent communicator; comfortable working with non-technical stakeholders. Thrive in chaos and love building zero-to-one . This isn’t just another job - it More ❯

Build and deploy AI/ML systems that boost accuracy, speed, and user experience. Partner with domain experts to turn complex workflows into AI-driven automation . Leverage LLMs, LangChain, and RAG at scale. Ship quickly, iterate fast, and set the foundation for our engineering culture . Requirements 2+ years in AI/ML engineering or applied research. Proven track … from idea → production with measurable impact. Deep hands-on expertise with LLMs (fine-tuning, prompt engineering, evaluation, and deployment at scale). Hands-on experience with PyTorch/TensorFlow, LangChain, vector databases , or similar tools. Excellent communicator; comfortable working with non-technical stakeholders. Thrive in chaos and love building zero-to-one . This isn’t just another job - it More ❯

Build and deploy AI/ML systems that boost accuracy, speed, and user experience. Partner with domain experts to turn complex workflows into AI-driven automation . Leverage LLMs, LangChain, and RAG at scale. Ship quickly, iterate fast, and set the foundation for our engineering culture . Requirements 2+ years in AI/ML engineering or applied research. Proven track … from idea → production with measurable impact. Deep hands-on expertise with LLMs (fine-tuning, prompt engineering, evaluation, and deployment at scale). Hands-on experience with PyTorch/TensorFlow, LangChain, vector databases , or similar tools. Excellent communicator; comfortable working with non-technical stakeholders. Thrive in chaos and love building zero-to-one . This isn’t just another job - it More ❯

Build and deploy AI/ML systems that boost accuracy, speed, and user experience. Partner with domain experts to turn complex workflows into AI-driven automation . Leverage LLMs, LangChain, and RAG at scale. Ship quickly, iterate fast, and set the foundation for our engineering culture . Requirements 2+ years in AI/ML engineering or applied research. Proven track … from idea → production with measurable impact. Deep hands-on expertise with LLMs (fine-tuning, prompt engineering, evaluation, and deployment at scale). Hands-on experience with PyTorch/TensorFlow, LangChain, vector databases , or similar tools. Excellent communicator; comfortable working with non-technical stakeholders. Thrive in chaos and love building zero-to-one . This isn’t just another job - it More ❯

vector stores (Chroma, FAISS, Milvus) with sensitive document ingestion pipelines - Host and optimise LLMs using vLLM/TGI on local GPU clusters without internet connectivity - Implement agent orchestration using LangChain/LangGraph in completely offline environments - Design secure document processing for classified materials with appropriate data sanitisation - Build monitoring and evaluation systems that operate within air-gapped infrastructure Essential Requirements … optimisation - Python expertise with offline dependency management and local package mirrors Technical Stack (All On-Premises) Models: Llama 3, Mistral, Qwen (locally hosted) Vector Stores: Chroma, FAISS, Milvus Orchestration: LangChain, LangGraph for agents Hosting: vLLM, TGI, Ollama on bare metal/private cloud Infrastructure: Air-gapped Kubernetes, local container registries Desirable Skills - Experience with defence/government IT security protocols More ❯

vector stores (Chroma, FAISS, Milvus) with sensitive document ingestion pipelines - Host and optimise LLMs using vLLM/TGI on local GPU clusters without internet connectivity - Implement agent orchestration using LangChain/LangGraph in completely offline environments - Design secure document processing for classified materials with appropriate data sanitisation - Build monitoring and evaluation systems that operate within air-gapped infrastructure Essential Requirements … optimisation - Python expertise with offline dependency management and local package mirrors Technical Stack (All On-Premises) Models: Llama 3, Mistral, Qwen (locally hosted) Vector Stores: Chroma, FAISS, Milvus Orchestration: LangChain, LangGraph for agents Hosting: vLLM, TGI, Ollama on bare metal/private cloud Infrastructure: Air-gapped Kubernetes, local container registries Desirable Skills - Experience with defence/government IT security protocols More ❯

vector stores (Chroma, FAISS, Milvus) with sensitive document ingestion pipelines - Host and optimise LLMs using vLLM/TGI on local GPU clusters without internet connectivity - Implement agent orchestration using LangChain/LangGraph in completely offline environments - Design secure document processing for classified materials with appropriate data sanitisation - Build monitoring and evaluation systems that operate within air-gapped infrastructure Essential Requirements … optimisation - Python expertise with offline dependency management and local package mirrors Technical Stack (All On-Premises) Models: Llama 3, Mistral, Qwen (locally hosted) Vector Stores: Chroma, FAISS, Milvus Orchestration: LangChain, LangGraph for agents Hosting: vLLM, TGI, Ollama on bare metal/private cloud Infrastructure: Air-gapped Kubernetes, local container registries Desirable Skills - Experience with defence/government IT security protocols More ❯

vector stores (Chroma, FAISS, Milvus) with sensitive document ingestion pipelines - Host and optimise LLMs using vLLM/TGI on local GPU clusters without internet connectivity - Implement agent orchestration using LangChain/LangGraph in completely offline environments - Design secure document processing for classified materials with appropriate data sanitisation - Build monitoring and evaluation systems that operate within air-gapped infrastructure Essential Requirements … optimisation - Python expertise with offline dependency management and local package mirrors Technical Stack (All On-Premises) Models: Llama 3, Mistral, Qwen (locally hosted) Vector Stores: Chroma, FAISS, Milvus Orchestration: LangChain, LangGraph for agents Hosting: vLLM, TGI, Ollama on bare metal/private cloud Infrastructure: Air-gapped Kubernetes, local container registries Desirable Skills - Experience with defence/government IT security protocols More ❯

vector stores (Chroma, FAISS, Milvus) with sensitive document ingestion pipelines - Host and optimise LLMs using vLLM/TGI on local GPU clusters without internet connectivity - Implement agent orchestration using LangChain/LangGraph in completely offline environments - Design secure document processing for classified materials with appropriate data sanitisation - Build monitoring and evaluation systems that operate within air-gapped infrastructure Essential Requirements … optimisation - Python expertise with offline dependency management and local package mirrors Technical Stack (All On-Premises) Models: Llama 3, Mistral, Qwen (locally hosted) Vector Stores: Chroma, FAISS, Milvus Orchestration: LangChain, LangGraph for agents Hosting: vLLM, TGI, Ollama on bare metal/private cloud Infrastructure: Air-gapped Kubernetes, local container registries Desirable Skills - Experience with defence/government IT security protocols More ❯

you What You’ll Do Design, implement, and ship production-grade LLM applications (prompting, RAG, evaluation, deployment). Develop and refine AI pipelines and retrieval systems using tools like LangChain, LangGraph, or custom frameworks. Own model evaluation frameworks to ensure quality, factuality, and performance across real-world workloads. Collaborate closely with the founding engineering team to build scalable infrastructure for … including 2–3+ years in AI/ML applications. Proven track record of shipping AI products into production (not just research or prototypes). Preferred tech stack - TypeScript, React, LangChain, and LLM orchestration. Experience with RAG systems , vector databases (e.g. Pinecone, PGVector, Weaviate), and model evaluation . Comfortable working in a fast-paced startup environment with a high degree of More ❯

you What You’ll Do Design, implement, and ship production-grade LLM applications (prompting, RAG, evaluation, deployment). Develop and refine AI pipelines and retrieval systems using tools like LangChain, LangGraph, or custom frameworks. Own model evaluation frameworks to ensure quality, factuality, and performance across real-world workloads. Collaborate closely with the founding engineering team to build scalable infrastructure for … including 2–3+ years in AI/ML applications. Proven track record of shipping AI products into production (not just research or prototypes). Preferred tech stack - TypeScript, React, LangChain, and LLM orchestration. Experience with RAG systems , vector databases (e.g. Pinecone, PGVector, Weaviate), and model evaluation . Comfortable working in a fast-paced startup environment with a high degree of More ❯

you What You’ll Do Design, implement, and ship production-grade LLM applications (prompting, RAG, evaluation, deployment). Develop and refine AI pipelines and retrieval systems using tools like LangChain, LangGraph, or custom frameworks. Own model evaluation frameworks to ensure quality, factuality, and performance across real-world workloads. Collaborate closely with the founding engineering team to build scalable infrastructure for … including 2–3+ years in AI/ML applications. Proven track record of shipping AI products into production (not just research or prototypes). Preferred tech stack - TypeScript, React, LangChain, and LLM orchestration. Experience with RAG systems , vector databases (e.g. Pinecone, PGVector, Weaviate), and model evaluation . Comfortable working in a fast-paced startup environment with a high degree of More ❯

you What You’ll Do Design, implement, and ship production-grade LLM applications (prompting, RAG, evaluation, deployment). Develop and refine AI pipelines and retrieval systems using tools like LangChain, LangGraph, or custom frameworks. Own model evaluation frameworks to ensure quality, factuality, and performance across real-world workloads. Collaborate closely with the founding engineering team to build scalable infrastructure for … including 2–3+ years in AI/ML applications. Proven track record of shipping AI products into production (not just research or prototypes). Preferred tech stack - TypeScript, React, LangChain, and LLM orchestration. Experience with RAG systems , vector databases (e.g. Pinecone, PGVector, Weaviate), and model evaluation . Comfortable working in a fast-paced startup environment with a high degree of More ❯

you What You’ll Do Design, implement, and ship production-grade LLM applications (prompting, RAG, evaluation, deployment). Develop and refine AI pipelines and retrieval systems using tools like LangChain, LangGraph, or custom frameworks. Own model evaluation frameworks to ensure quality, factuality, and performance across real-world workloads. Collaborate closely with the founding engineering team to build scalable infrastructure for … including 2–3+ years in AI/ML applications. Proven track record of shipping AI products into production (not just research or prototypes). Preferred tech stack - TypeScript, React, LangChain, and LLM orchestration. Experience with RAG systems , vector databases (e.g. Pinecone, PGVector, Weaviate), and model evaluation . Comfortable working in a fast-paced startup environment with a high degree of More ❯

in small teams (links to repos, case studies, or live services). Desired Node.js alongside Python for services or integrations. Experience with vector databases (e.g., Chroma) and embedding pipelines. LangChain or CrewAI for orchestration; MCP servers for integrations. Security hygiene (secrets, permissions, least-privilege) and practical data-privacy basics. Planning & execution in Linear (or similar). Tools & Stack Backend/… Redis (caching/sessions). Vectors/Embeddings: Chroma (or similar). AI Models & APIs: Claude (Anthropic), Gemini (Google); Amazon Nova Canvas (vision), Deepgram (audio). AI Dev Tools: LangChain or CrewAI (orchestration), MCP servers (integration), GitHub Copilot/Claude Code. Infrastructure: AWS (serverless functions), Docker (primarily for custom MCPs). Frontend (when needed): React/Next.js (for dashboards/ More ❯