1 to 25 of 135 LangChain Jobs in the UK

Conversational AI development Model training, testing and evaluation Prompt Engineering and AI workflow optimisation Programming & Frameworks Strong Python development skills PyTorch TensorFlow Scikit-Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such as Pinecone, Weaviate ...

multimodal models, and earlier architectures such as GANs and VAEs. Experience across text, code, image, and multimodal generation; advanced prompt engineering; orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel). Hands‐on exposure to both API‐based (Claude, GPT, Gemini) and open‐source (Llama, Mistral) LLM‐based solution design. Agentic ...

Azure, GCP) and modern data stack technologies. Technical Expertise: AI/GenAI: LLM integration, prompt engineering, RAG architectures, fine-tuning, Agentic AI frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering: ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms: AWS (SageMaker, Bedrock, Glue), Azure ...

Azure, GCP) and modern data stack technologies. Technical Expertise: AI/GenAI: LLM integration, prompt engineering, RAG architectures, fine-tuning, Agentic AI frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering: ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms: AWS (SageMaker, Bedrock, Glue), Azure ...

Azure, GCP) and modern data stack technologies. Technical Expertise: AI/GenAI: LLM integration, prompt engineering, RAG architectures, fine-tuning, Agentic AI frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering: ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms: AWS (SageMaker, Bedrock, Glue), Azure ...

Azure, GCP) and modern data stack technologies. Technical Expertise: AI/GenAI: LLM integration, prompt engineering, RAG architectures, fine-tuning, Agentic AI frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering: ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms: AWS (SageMaker, Bedrock, Glue), Azure ...

Azure, GCP) and modern data stack technologies. Technical Expertise: AI/GenAI: LLM integration, prompt engineering, RAG architectures, fine-tuning, Agentic AI frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering: ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms: AWS (SageMaker, Bedrock, Glue), Azure ...

Azure, GCP) and modern data stack technologies. Technical Expertise: AI/GenAI : LLM integration, prompt engineering, RAG architectures, fine-tuning, Agentic AI frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure ...

Azure, GCP) and modern data stack technologies. Technical Expertise: AI/GenAI : LLM integration, prompt engineering, RAG architectures, fine-tuning, Agentic AI frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure ...

Azure, GCP) and modern data stack technologies. Technical Expertise: AI/GenAI : LLM integration, prompt engineering, RAG architectures, fine-tuning, Agentic AI frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure ...

Azure, GCP) and modern data stack technologies. Technical Expertise: AI/GenAI : LLM integration, prompt engineering, RAG architectures, fine-tuning, Agentic AI frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure ...

selecting the right model for use case, cost, and performance constraints. Hands‐on experience building Gen AI applications using modern frameworks such as LangChain, LangGraph, LlamaIndex, and Hugging Face, including agentic and multi‐step workflows. Proven experience designing and implementing Retrieval‐Augmented Generation (RAG) systems, including vector databases (pgvector, Pinecone ...

selecting the right model for use case, cost, and performance constraints* **Hands‐on experience building Gen AI applications using modern frameworks** such as LangChain, LangGraph, LlamaIndex, and Hugging Face, including agentic and multi‐step workflows* **Proven experience designing and implementing Retrieval‐Augmented Generation (RAG) systems**, including vector databases (pgvector, Pinecone ...

experience ·Applied AI engineering, ML engineering or software engineering background ·Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning ·Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks ·Experience with vector databases such as Pinecone, Chroma or similar ·API development experience, ideally with FastAPI or similar frameworks ...

experience · Applied AI engineering, ML engineering or software engineering background · Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning · Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks · Experience with vector databases such as Pinecone, Chroma or similar · API development experience, ideally with FastAPI or similar frameworks ...

pipelines, ETL, ELT, APIs, REST APIs, LLM, large language models, LLM APIs, OpenAI, Azure OpenAI, prompt engineering, retrieval augmented generation, RAG, vector databases, embeddings, LangChain, LlamaIndex, agentic AI, AI agents, workflow automation, machine learning, model evaluation, model monitoring, MLOps, Power BI, DAX, Power Query, data modelling, data quality, data lineage ...

teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems Experience designing and scaling low-latency, customer ...

Bonus Points Experience with any of the following would be highly advantageous: AI gateways and model routing Prompt management platforms AI evaluation frameworks LangGraph, LangChain, LlamaIndex, DSPy, CrewAI or similar orchestration frameworks Vector databases and semantic retrieval Knowledge graphs or document understanding systems Building internal AI platforms used by multiple ...

client proposals Candidates should have strong experience in AI Engineering, MLOps and cloud-native AI platforms, alongside hands-on knowledge of technologies such as LangChain, LlamaIndex, MLflow, Kubernetes, Docker and CI/CD tooling. Applicants will ideally demonstrate: * Experience working in a major Consulting firm, and/or in industry ...

core ML—supervised, unsupervised, evaluation, regularisation, statistics Production ML experience—deploying, serving and monitoring models at scale LLM and generative AI tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows) MLOps platforms (MLflow, Kubeflow, Vertex AI, SageMaker, Databricks or equivalent) Cloud experience ...

management on AKS. Strong hands‐on experience with Azure, including Azure OpenAI, Azure AI Search, AKS, and Databricks. Proven production experience with LangGraph and LangChain, including multi‐step agentic workflows and tool‐calling agents. Hands‐on experience with Azure AI Search or other vector/hybrid search solutions, including vector ...

grade AI solutions using Python , .NET , and cloud-based MLOps pipelines. Direct teams leveraging advanced frameworks including PyTorch , TensforFlow , Hugging Face , ONNX Runtime , and LangChain , integrating orchestration tools like Semantic Kernel , LangGraph , and CrewAI Drive responsible integration of Large Language Models (LLMs) from OpenAI , Anthropic , Google Gemini , and Mistral , including ...

Vertex AI). Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic frameworks (LangChain, LangGraph, Semantic Kernel). Data pipelines: data lake/lakehouse architectures, ETL/ELT, and data quality/lineage tooling that feed AI systems. Automation, Orchestration & Observability ...

engineering, data, DevOps and business teams - Advise clients on AI platform capability and implementation strategy Tech environment: Python LLMs (prompt engineering, fine-tuning, RAG) LangChain/LangGraph Agent frameworks Vector databases MLOps/LLMOps AWS/Azure/GCP/Databricks Kubernetes & GPU infrastructure What you'll bring: - Experience designing ...

with engineering, data, DevOps and business teams Advising clients on AI platform capability and implementation strategy Environment Python LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise ...