You will work with backend development, databases, APIs, cloud services and production machine learning systems. This is for a growing technology business. No specific project or team size is mentioned.

A Senior AI Engineer at Stakemate will use agent frameworks (LangGraph, LlamaIndex, Semantic Kernel, ADK), RAG, Python, cloud services (Azure/GCP/AWS), and SQL to move AI from experiments to production. They will shape the platform and architecture for a live betting product at a fast-growing social sports betting startup.

You will work with agent frameworks (LangGraph, LlamaIndex, Semantic Kernel, ADK), RAG pipelines, vector stores, Python, SQL, and a major cloud (Azure AI Foundry, GCP, or AWS). You will take AI agents from proof-of-concept to production within Stakemate’s live sports betting product, setting the governance and standards for the company’s AI estate. Reporting to the CTO, you will shape the platform and architecture as the company scales.

Python, PyTorch, JAX, LLMs, vLLM, vector databases and modern agent frameworks will be used. The stealth AI startup is building a pre-launch, next-generation AI assistant for everyday tasks, conversations and workflows — a 0-to-1 opportunity on a small engineering team.

Design, build and deploy production Generative AI applications, LLM-powered solutions and agentic frameworks using Python, LangChain, LangGraph, and OpenShift. You will automate enterprise workflows with intelligent agents, working with PostgreSQL and pgvector as part of Citi’s COO-Technology team building scalable AI for global operations. This is an Individual Contributor Staff Engineer role.

Moody's★3.6 (589)· London

You will work with Python, TypeScript, Java, or Go; cloud platforms (AWS, GCP, Azure); Docker, Kubernetes, PostgreSQL, MongoDB, Redis, vector databases; and build AI applications using LLMs, RAG, prompt engineering, and AI agents. The Innovation team builds next-generation internal and external products powered by large language models, AI agents, machine learning, and natural language processing.

Edited★2.7 (3)· London

You will work with Python, *nix, LLMs, MCP, Django, Flask, FastAPI, Elasticsearch, and SQL databases. You will build an AI chatbot with agents and tooling, and scale a large-scale retail data infrastructure on AWS and bare metal for the company's AI-driven retail intelligence platform.

Senior WordPress Developer role: build bespoke WordPress sites and apps using PHP, MySQL, ACF, WooCommerce, Gutenberg, JavaScript (ES6+), SASS/SCSS, Git, Composer, npm, Vite, CI/CD. You’ll also drive AI-assisted development (RAG, MCP, Copilot) and mentor junior developers.

You will work with React/Next.js/TypeScript and Python on an agentic AI platform that ingests sustainability data, runs scenarios and recommends actions. The company is building a workflow and decision-making layer for sustainability, using AI agents and a knowledge context graph.

This role works with AI agents, LLMs, tool/function calling, RAG, prompt engineering, orchestration, AWS, and APIs. You will design and deploy agentic solutions for manufacturing value chains (e.g., P2P, O2C), integrating with ERP, PLM, and sourcing tools like Ariba. QAD provides enterprise software for global manufacturers.

QAD★4.2 (54)· London

You will work with LLMs, tool/function calling, RAG, prompt engineering, orchestration, evals, AWS cloud, APIs, and enterprise data integration patterns. You design and deploy AI agents for manufacturing value chains (P2P, O2C, S2C, P2M), integrating with ERP, PLM, EDI, and sourcing tools like Ariba and Coupa.

Build AI agents, LLM apps, and automation workflows using Python, TypeScript, or JavaScript. You will apply retrieval, tool calling, evaluations, and guardrails to build AI-native systems for BJAK’s AI Neobank app, automating onboarding, support, KYC, risk review, and operations.

This role develops generative AI applications using Java, Python, React or Angular, LangChain, LlamaIndex, Hugging Face, Docker, Kubernetes, and AWS, with tools like GitHub Copilot. You will build scalable, AI-powered solutions for Citi’s global finance operations.

You'll work with Python, C#, SQL, REST APIs, cloud platforms (Azure, AWS, Snowflake), CI/CD, Docker, and Git. You'll join a dedicated AI squad building and shipping production-grade AI-powered applications using Generative AI, LLMs, agentic AI, and prompt engineering for an investment management firm.

You will work with Python, Django, Django REST Framework, FastAPI, PostgreSQL, AWS, React.js, Docker, Redis, Celery, Pandas, NumPy, Git, Jenkins, Elasticsearch, and Kubernetes, using AI tools like Claude Code and Cursor. You’ll shape the technical direction of a cloud-based property management platform handling payments, quoting, invoicing, booking, search, data pipelines, notifications, and fraud prevention. This is a leadership role bridging product vision and technical execution, guiding engineers toward delivery.

Lead a hands-on founding engineering role building AI agents for data privacy compliance at Pyxos. Own the control plane, agent architecture, model-abstraction layer, telemetry, evaluation harnesses, and expert knowledge system using LLMs, multi-step agentic workflows, and CI/CD pipelines. You will work with a production system serving enterprise customers, hiring a deliberately small team as the most senior technical leader reporting to the CEO.

Lead AI engineers use Python, LangChain, vector stores, and LLMOps tooling to build and operate production generative AI applications like copilots and agentic workflows. They design RAG pipelines, own end-to-end development, and integrate with enterprise data systems and APIs. This player-coach role seeds and grows the AI Engineering function within GCG technology at Capital Group, a global investment firm.

You’ll use Python, LLMs, RAG pipelines, embeddings, vector storage, and cloud-native tools to build production generative AI applications—copilots, assistants, and agentic workflows—that improve Capital Group’s investment process.

Design, build

You will architect core services using React and Python, and develop AI agents with Agentic AI, RAG, and prompt engineering for text-based LLM applications. The team is building a platform that automates end-to-end intelligence investigation workflows, moving beyond data aggregation to deliver tailored insights.

You'll work with Python, TypeScript, C#, Azure, React/Angular, Power BI, Copilot Studio, Claude Cowork, LangChain, LangGraph, and AI orchestration frameworks. You'll design, build, and scale AI agents, automation workflows, integrations, APIs, and RAG pipelines for a professional services organisation investing in AI and cloud technology.

Accenture★3.9 (29k)· London

Works with AI platforms (Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, Palantir) and cloud-native tools (APIs, microservices, containerization, serverless) plus agentic solutions (agents, orchestration, RAG). Embedded inside client enterprises to deploy, scale, and operationalize AI platforms, owning production outcomes from prototype to working system.

You will use Python (Django/FastAPI), Docker, Kubernetes, and CI/CD to build, deploy, and scale production AI features including RAG systems and multi-agent infrastructure, along with backend services, data pipelines, and Redis-backed queues. This is a foundational role at an AI platform that builds mission-critical, enterprise-grade AI for regulated environments. You will report directly to the founders.

The role involves C#, ASP.NET Core, async/await, Entity Framework Core, Git, and optionally Azure DevOps, Docker, and Playwright. You will build backend services, integration layers, and AI API integrations for large-scale websites, apps, and platforms delivered to global brands.

Build scalable backend services and APIs with Go, Python, or C++, and develop frontend applications using React and TypeScript. You will ship AI-powered product features end-to-end on a platform combining computer vision, multimodal AI, and real-time data. Work closely with AI and platform engineers on new capabilities within a small, experienced team.