1 to 25 of 604 OpenAI Jobs in England

develop AI/GenAI applications, Agentic AI workflows, and RAG-based solutions.Build scalable Python services, APIs, and AI orchestration components.Implement solutions using Azure OpenAI, OpenAI, AWS Bedrock, Vertex AI, and open-source LLMs.Develop and optimize RAG pipelines, vector databases, and semantic search capabilities.Collaborate with cloud, data, DevOps, and architecture teams … hands-on experience with Python, Generative AI, Agentic AI, LLMs, and RAG architectures.Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks.Expertise in Azure OpenAI, OpenAI, AWS Bedrock, Vertex AI, or open-source LLM ecosystems.Knowledge of REST APIs, microservices, cloud platforms (Azure/AWS/GCP), Docker, Kubernetes ...

Engineering, Responsible AI, and AI Evaluation Frameworks. Experience with LangChain, LangGraph, Semantic Kernel, and AutoGen. Hands-on experience with Azure AI Foundry/Azure OpenAI, AWS Bedrock and SageMaker, Google Vertex AI, and hybrid and multi-cloud architectures. Strong programming experience with Python, Java, Scala, TypeScript, and SQL. Experience with ...

applications, and internal tools. Integrate AI capabilities following secure, scalable engineering best practices. Design, build and validate AI‐driven solutions leveraging providers such as OpenAI and Anthropic. Enhance low‐code/no‐code automation platforms (e.g., Power Automate, n8n, Workato) by embedding intelligent processing and applying agentic patterns where relevant. ...

LangChain, LangGraph, Semantic Kernel, or similar frameworks. Solid understanding of NLP, machine learning, and deep learning concepts. Hands‐on experience with Azure AI, Azure OpenAI, AWS, or Google Cloud AI services. Experience with Docker, Git, and CI/CD. Bachelor's degree in Computer Science, Artificial Intelligence, Data Science ...

ability to work in client-facing delivery environments. Background in solution design, enterprise architecture, or technical consulting. Desirable Skills Experience with LangChain, LlamaIndex, Azure OpenAI, AI Foundry, GPT-4, Claude, LLaMA, Hugging Face, MLflow, Airflow, KServe, FAISS, Chroma, or similar technologies. Experience designing multi-agent workflows and autonomous LLM integrations. ...

model observability, monitoring, evaluation frameworks, experimentation, reliability, and operational perfection. Expertise in cloud‐native AI development using Azure AI Foundry, Azure Machine Learning, Azure OpenAI, Azure AI Search, AWS AI Services, and modern cloud architectures. Experience implementing MLOps and LLMOps practices, including CI/CD, model lifecycle management, governance ...

shaping enterprise AI architecture, standards and governance while building innovative AI solutions that deliver business value. Working hands-on with Azure AI Foundry, Azure OpenAI, Claude and open-source large language models, you'll design and deploy enterprise-scale AI products using agentic AI, RAG, vector search and machine learning … minimum, we are looking for: AI & GenAI Platform Leadership – Excellent experience designing and delivering AI solutions using Azure AI Foundry, Azure OpenAI, OpenAI, Azure AI Search, Claude and open-source LLMs, driving adoption across enterprise platforms. Engineering Leadership & Delivery – Deep software engineering expertise, strong Python skills, and hands-on delivery ...

OpsStrong experience with Azure and/or AWS cloud platforms.Hands-on experience supporting AI, ML or Generative AI solutions in production.Knowledge of Azure OpenAI, Azure AI Services, Amazon Bedrock and/or SageMaker.Understanding of LLMs, RAG architectures, AI Agents and modern AI patterns.Experience in Platform Engineering, DevOps and cloud operations.CI ...

Pinecone, Weaviate, FAISS, Azure AI Search). Hands‐on experience with AWS Bedrock and Sagemaker would be highly desirable Experience with GenAI platforms (e.g., OpenAI API, Anthropic, Gemini, Llama or equivalents). Exposure to big data/distributed computing and pipeline/feature engineering. LLM safety & governance (hallucination mitigation, grounded ...

advantage. AI architecture: Experience setting AI and solution architecture, reference designs and engineering standards. AI tooling: Experience with Azure AI Foundry, Azure OpenAI and Azure AI Search, or equivalent AI services on another enterprise cloud. Enterprise Platform Design: 7+ years of demonstrated track record designing enterprise data architectures and data ...

agentic AI applications and multi-agent systems on Azure using Microsoft Foundry (formerly Azure AI Foundry) and the Azure AI Services portfolio, including Azure OpenAI, Azure AI Search and Azure AI Document Intelligence.Develop production-grade AI-enabled services and APIs in Python and C#/.NET, integrating agents and models ...

methodologies and modern software delivery practices AI Fluency – Experience or familiarity with integrating AI-powered capabilities into software applications, including LLM APIs such as OpenAI, AWS Bedrock, Anthropic, or similar platforms. Understanding of concepts such as prompt engineering, retrieval-augmented generation (RAG), AI agents, and responsible AI practices, with ...

methodologies and modern software delivery practices AI Fluency - Experience or familiarity with integrating AI‐powered capabilities into software applications, including LLM APIs such as OpenAI, AWS Bedrock, Anthropic, or similar platforms. Understanding of concepts such as prompt engineering, retrieval‐augmented generation (RAG), AI agents, and responsible AI practices, with ...

strong fundamentals in data structures, algorithms, and system design Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API) Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure Strong problem-solving skills with the ability to navigate ambiguous requirements ...

prompt engineering, tool and function calling, RAG, and at least one production Agentic AI system. Cloud AI platform : deep experience with one of Azure, OpenAI, AWS Bedrock, Claude; Kubernetes and cloud-native deployment. LLMOps & evaluation : CI/CD for AI, automated evals, experiment tracking, observability, model lifecycle management. Responsible ...

enterprise AI architectures, multi-agent frameworks, and RAG pipelines across operational workflows. Agentic AI & LLMs: Build and deploy agents using modern foundation models (Claude, OpenAI) featuring tool calling, structured outputs, and autonomous multi-agent coordination. Agentified Dashboards: Develop interactive, natural-language interfaces and dashboards (R Shiny or Python) over portfolio ...

enterprise AI architectures, multi-agent frameworks, and RAG pipelines across operational workflows. Agentic AI & LLMs: Build and deploy agents using modern foundation models (Claude, OpenAI) featuring tool calling, structured outputs, and autonomous multi-agent coordination. Agentified Dashboards: Develop interactive, natural-language interfaces and dashboards (R Shiny or Python) over portfolio ...

FastAPI, Pydantic, asyncio, pandas, pytest). Experience with R and R Shiny for building and deploying applications. Hands-on expertise with LLM APIs (e.g., OpenAI, Anthropic Claude) and agent frameworks (e.g., LangGraph, CrewAI). Advanced SQL skills and familiarity with Snowflake and REST API integrations. Knowledge of engineering practices such ...

FastAPI, Pydantic, asyncio, pandas, pytest). Experience with R and R Shiny for building and deploying applications. Hands-on expertise with LLM APIs (e.g., OpenAI, Anthropic Claude) and agent frameworks (e.g., LangGraph, CrewAI). Advanced SQL skills and familiarity with Snowflake and REST API integrations. Knowledge of engineering practices such ...

Shiny : Solid R and experience building and deploying Shiny applications. LLM and agent engineering: Hands-on experience with LLM APIs (Anthropic Claude, OpenAI or similar), tool calling and connector patterns, RAG and vector search, agent frameworks (for example LangGraph, CrewAI or AutoGen) and LLM evaluation. Data and integration: Advanced ...

Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), AI agents, or machine learning workflows. Experience integrating AI APIs and platforms such as OpenAI, Anthropic, Azure AI, or similar technologies. Knowledge of vector databases, embeddings, prompt engineering, and AI application architecture. Experience with Python for AI/ML-related ...

practices: design, testing, code review, CI/CD, Git & GitHub Hands‐on experience with agentic AI frameworks (examples include LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI’s Agents SDK, and Google’s Agent Development Kit) and MCP (Model Context Protocol) Practical experience building RAG/LLM‐based pipelines and working with ...

methodologies and modern software delivery practices AI Fluency - Experience or familiarity with integrating AI-powered capabilities into software applications, including LLM APIs such as OpenAI, AWS Bedrock, Anthropic, or similar platforms. Understanding of concepts such as prompt engineering, retrieval-augmented generation (RAG), AI agents, and responsible AI practices, with ...

genuinely used, rather than pilots. Strong practical experience with LLM and agent frameworks such as Microsoft Copilot Studio, Azure AI Foundry, Azure OpenAI, Semantic Kernel,LangChain,LangGraph,AutoGenorCrewAI, and with core agent patterns including tool calling, orchestration, memory, multi agent workflows and retrieval augmented generation. Experience with workflow and process ...

methodologies and modern software delivery practices AI Fluency - Experience or familiarity with integrating AI-powered capabilities into software applications, including LLM APIs such as OpenAI, AWS Bedrock, Anthropic, or similar platforms. Understanding of concepts such as prompt engineering, retrieval-augmented generation (RAG), AI agents, and responsible AI practices, with ...