1 to 25 of 82 OpenAI Jobs in the City of London

Strong programming skills in Python; proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms More ❯

Strong programming skills in Python; proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms More ❯

applications using LLMs, utilizing frameworks such as LangChain, LlamaIndex, etc and productionizing machine learning and AI models. Language Model Development: Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. Cloud Computing Expertise: Proven architect kind of experience in cloud computing, particularly with Azure Cloud Services. Technical Proficiency: Strong skills in UNIX/Linux More ❯

applications using LLMs, utilizing frameworks such as LangChain, LlamaIndex, etc and productionizing machine learning and AI models. Language Model Development: Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. Cloud Computing Expertise: Proven architect kind of experience in cloud computing, particularly with Azure Cloud Services. Technical Proficiency: Strong skills in UNIX/Linux More ❯

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 management of More ❯

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 management of More ❯

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 management of More ❯

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 problem More ❯

and user experience. Develop and integrate agentic frameworks, RAG pipelines, and vector database architectures to support natural language and intelligent automation use cases. Fine-tune and customise LLMs (e.g. OpenAI, Anthropic, and other models) for specific business applications. Collaborate with engineering and data science teams to implement MLOps best practices — from deployment and monitoring to continuous iteration. Partner with commercial More ❯

and user experience. Develop and integrate agentic frameworks, RAG pipelines, and vector database architectures to support natural language and intelligent automation use cases. Fine-tune and customise LLMs (e.g. OpenAI, Anthropic, and other models) for specific business applications. Collaborate with engineering and data science teams to implement MLOps best practices — from deployment and monitoring to continuous iteration. Partner with commercial More ❯

applications using Azure AI and ML. Requirements Proven experience in AI/ML solutions on Azure, ideally with Generative AI. Expertise with Azure AI, Azure Machine Learning, and Azure OpenAI Service. Strong Python and PyTorch. Experience of RAG pipeline deployment, prompt engineering, fine-tuning foundation models. Knowledge of Responsible AI principles and AI governance. Strong understanding of cloud-native deployment More ❯

applications using Azure AI and ML. Requirements Proven experience in AI/ML solutions on Azure, ideally with Generative AI. Expertise with Azure AI, Azure Machine Learning, and Azure OpenAI Service. Strong Python and PyTorch. Experience of RAG pipeline deployment, prompt engineering, fine-tuning foundation models. Knowledge of Responsible AI principles and AI governance. Strong understanding of cloud-native deployment More ❯

Understanding of modern development best practices, including agile delivery, CI/CD, and automated testing. Passion for emerging tech and willingness to learn Generative AI and LLM technologies (e.g. OpenAI, Claude). ✨ Nice-to-haves: Experience working in or with legal tech, consulting, or data-driven environments. Familiarity with UX design principles and the ability to prototype interfaces. Experience managing More ❯

Understanding of modern development best practices, including agile delivery, CI/CD, and automated testing. Passion for emerging tech and willingness to learn Generative AI and LLM technologies (e.g. OpenAI, Claude). ✨ Nice-to-haves: Experience working in or with legal tech, consulting, or data-driven environments. Familiarity with UX design principles and the ability to prototype interfaces. Experience managing More ❯

Azure AI Engineer Associate, GCP AI/ML Engineer). Vendor-specific CX/CCaaS certifications (Genesys Cloud, Amazon Connect). Specialist AI/ML certifications (TensorFlow, Hugging Face, OpenAI, or equivalent). Benefits This is your chance to join a friendly and passionate team that will motivate you to learn and develop your career in a growing company. Benefits More ❯

Azure AI Engineer Associate, GCP AI/ML Engineer). Vendor-specific CX/CCaaS certifications (Genesys Cloud, Amazon Connect). Specialist AI/ML certifications (TensorFlow, Hugging Face, OpenAI, or equivalent). Benefits This is your chance to join a friendly and passionate team that will motivate you to learn and develop your career in a growing company. Benefits More ❯

a media agency, consultancy, or fast-paced business. Strong programming skills in Python, with experience building automation workflows, APIs, and data pipelines. Exposure to AI/ML frameworks (e.g. OpenAI, LangChain, TensorFlow, PyTorch). Solid knowledge of SQL and data warehousing concepts. Demonstrated experience with cloud platforms ( GCP & Azure preferred). Strong understanding of data modelling, transformation, and orchestration (e.g. More ❯

a media agency, consultancy, or fast-paced business. Strong programming skills in Python, with experience building automation workflows, APIs, and data pipelines. Exposure to AI/ML frameworks (e.g. OpenAI, LangChain, TensorFlow, PyTorch). Solid knowledge of SQL and data warehousing concepts. Demonstrated experience with cloud platforms ( GCP & Azure preferred). Strong understanding of data modelling, transformation, and orchestration (e.g. More ❯

ML/DL libraries (TensorFlow, PyTorch, scikit-learn, Pandas). Practical experience with RAG or agentic AI frameworks (LangChain, LlamaIndex). Experience working with LLM APIs (e.g. Hugging Face, OpenAI). Exposure to conversational AI platforms (Dialogflow, Lex, Rasa, etc.). Ability to work collaboratively in fast-paced, agile, and multidisciplinary environments. Excellent communication skills and a strong interest in More ❯

ML/DL libraries (TensorFlow, PyTorch, scikit-learn, Pandas). Practical experience with RAG or agentic AI frameworks (LangChain, LlamaIndex). Experience working with LLM APIs (e.g. Hugging Face, OpenAI). Exposure to conversational AI platforms (Dialogflow, Lex, Rasa, etc.). Ability to work collaboratively in fast-paced, agile, and multidisciplinary environments. Excellent communication skills and a strong interest in More ❯

management Ability to establish coding standards and best practices across teams AI/ML Expertise Strong understanding of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) Experience with LLM integration (OpenAI, Anthropic, open-source models) Knowledge of RAG architectures, prompt engineering, and vector databases (Pinecone, Weaviate) Experience with MLOps tools and monitoring model performance in production Automation Architecture Deep knowledge of More ❯

Front-End: React/Next.js (TypeScript preferred) Back-End: Node.js/Express/Firebase/Supabase Cloud & DevOps: Microsoft Azure + GitHub Actions for automation and deployment AI Integration: OpenAI API (GPT-4 Turbo), LangChain, Azure AI Foundry Analytics: Power BI/Chart.js for real-time progress tracking Integrations: LTI with Microsoft Teams and Google Classroom Speech: Azure Speech and More ❯

API design, data modelling, and microservice architecture. Excellent communication skills, with the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and comprehensive More ❯

API design, data modelling, and microservice architecture. Excellent communication skills, with the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and comprehensive More ❯

on software development experience (Python preferred; additional exposure to JavaScript/TypeScript or Go beneficial). Strong background in AI systems, cloud-native architectures, and modern ML tooling (LangChain, OpenAI API, vector stores, RAG pipelines). Experience designing distributed, high-availability platforms deployed on AWS or similar cloud environments. Excellent communication and stakeholder management skills, with the ability to translate More ❯