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.

Work with Java, GitHub Copilot, Devin.AI, Citi Squad, Stylus Workspaces (Gemini, OpenAI, Claude, Llama), Docker, Kubernetes, and CI/CD. Build high-performance, real-time FX risk management systems for a greenfield platform with a 10+ year strategic commitment. As a VP, lead end-to-end delivery and technical direction.

You'll work with Python, NLP/LLMs, SQL/NoSQL databases, and cloud infrastructure, designing retrieval, knowledge-base, and reasoning models. You own projects end-to-end at Catapult, which builds personalised AI that understands a user's full work context across email, calendar, Slack, and other tools. No team size is given for this founding role.

You'll work with Python, building and deploying LLM-powered systems from scratch. As one of the first technical hires, you'll design and shape AI systems that solve a real-world problem, collaborating directly with the founding team.

Wolf & Badger★3.0 (3)· London

Senior Product Manager — Wolf & Badger. Work with AI agents, LLMs, APIs, MCP, commerce and integration platforms, plus structured product data, payments and fulfilment infrastructure. Own the product strategy for the agentic-commerce platform that powers the marketplace’s distribution channels, retail media, brand integrations and partner connectivity. You will be the sole product manager on this remit, working with a team of c.10 engineers and the VP Technology.

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.

Design, build

You’ll build automations, agents, and tooling using Python, TypeScript, APIs, LLMs (agents, tool use, retrieval), and databases for an AI-powered front desk product that answers calls, emails, and messages for UK letting agents. You will automate lead sourcing, enrichment, scoring, CRM hygiene, and pipeline reporting for the commercial team.

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.

Work with AI/ML systems, agentic workflows, LLMs, and enterprise data/automation platforms. You will design and deliver scalable, AI-powered solutions that help enterprises use data and automation for decision-making, partnering with clients from concept through execution.

Work with Python, modern ML tooling, and LLM inference infrastructure to build and deploy specialized AI agents. You will own the end-to-end AI/ML stack for a research-led company that builds simulations and language models for social science and public policy problems.

Work with TypeScript, LangChain, React, GraphQL, Prisma, Temporal, and LlamaIndex to build AI agents that automate high-stakes banking workflows. You will own features end-to-end, architecting a core platform that orchestrates AI, customers, and humans to replace legacy banking bottlenecks.

Build full-stack features with Node.js, React, and TypeScript, and design AI-powered capabilities using LLMs and workflow orchestration, utilizing AI coding tools like Claude Code. The company is an early-stage startup using AI to help organizations modernize supporter engagement, operational workflows, and data usage.

Wise★3.5 (42)· London

Build backend

Equinix★3.7 (391)· London

You will design and ship LLM-powered agents and the platform they run on using Python or TypeScript, APIs, microservices, event-driven architecture, Git, CI/CD, and cloud platforms, with tools like MCP and A2A. The Equinix Incubation team builds agentic systems that automate the software delivery lifecycle end to end—from intake and business case through code, test, release, and value tracking—with humans directing every gate.

Samsung Electronics★3.9 (10k)· London

You'll work with Python, RAG, vector databases, AWS Bedrock, Claude, and agentic frameworks (LangGraph, CrewAI) to build GenAI automation for Sales, Marketing, Finance, HR, Legal, and Operations. You'll architect agentic workflows and multi-agent orchestration, owning the end-to-end AI lifecycle on a small, senior, high-trust team.

You will design and productionise retrieval and knowledge-base systems, reasoning models, and live-screen-context models using Python, cloud infrastructure, and SQL/NoSQL databases. The company builds a proactive AI assistant that maintains a living model of a user’s entire digital workspace—email, messages, meetings, documents—to act on their behalf. This is a founding role in a small team of repeat founders with a product in private alpha.

You'll work with PyTorch, distributed training, Docker/K8s/IaC, and Python backend. The company builds foundation models for extreme physics to accelerate progress in semiconductors, aerospace, defence, and fusion. Joining a small, research-heavy team, you'll be the first dedicated engineering owner for the ML stack.

Fletchers Solicitors★4.1 (83)via Jack & Jill· London

You will work with Python, FastAPI, Azure, and Fly.io to design scalable backend applications and data pipelines for Fletch AI, a suite of NLP and LLM-based tools that automate legal claims in personal injury and clinical negligence. As a player-coach, you will lead a team of 8+ engineers, overseeing technical direction, site reliability, and production deployment of ML models.

You’ll work with Kotlin, TypeScript, Azure, Terraform, Temporal, and Postgres to build large-scale batch processing infrastructure, an LLM gateway, and enterprise-grade auth/observability for an AI operating system that automates analysis and documentation of complex enterprise software environments. You join a small, talent-dense backend team owning significant core platform components.

Design agentic AI systems and perform prompt engineering for life science tasks like clinical trial landscaping and regulatory monitoring. You will bridge pharma enterprise clients and engineering, automating complex data workflows for a platform already used by paying customers.

You will use Python or JavaScript with low-code platforms like Zapier or n8n and integrate LLMs and AI via REST APIs. You will identify and automate manual inefficiencies across the business, building internal automation ecosystems at Goodlord, a platform used by around 3,000 letting agents.

Build and launch AI-powered products using TypeScript, React, Node.js, Rust, Azure, Docker, and LLM APIs (OpenAI, Anthropic). As the founding product engineer, you’ll own the full stack—from frontend and backend to AI workflows—and work directly with founders to shape product direction from 0 to 1.