AI & Data Engineer

AI & Data Engineer Remote (UK-based) | Full-Time About Us Ironwood Digital is the 2026 OTC Trading Platform of the Year (). Our network handles over $50 billion in daily trading volumes across FX, Equities, and Cryptocurrency, connecting 40+ of the world's leading liquidity providers. We build trading systems that operate at the edge of what's technically possible — where nanoseconds matter and a dropped message costs real money. Our engineering team is small, senior, and deeply invested in the craft of building cutting edge, reliable, high-performance systems. The Role We're looking for a full-stack engineer who can build AI-powered tools and data infrastructure that make our platform smarter, our people more effective, and our operations more scalable. This is not a research role. You'll build real systems that people use every day — Slack bots that investigate production incidents, data pipelines that surface anomalies before clients notice them, and AI agents that turn hours of manual trawling into seconds of guided investigation. You'll work across the full stack: Python and TypeScript for AI tooling and integrations, Go for backend services, and SQL for data analysis and pipeline work. The person we're looking for ships working software, cares about making people's lives easier, and is energised by the pace of the AI landscape. You don't need to have built LLM applications before — but you should be curious, practical, and comfortable learning fast. You'll work closely with our TechOps, Connectivity, and Data teams to understand their workflows, pain points, and knowledge gaps — then build the tools and infrastructure that solve them. This is a high-leverage role: the systems you build will multiply the effectiveness of every engineer and operator in the company. What You'll Work On AI-powered investigation tools — Slack-based bots and agents that automatically analyse support tickets, query production logs, and surface relevant context for incident response MCP (Model Context Protocol) servers — authenticated access to ClickHouse, Kubernetes, Atlassian, and GitHub, enabling AI agents to interact with real systems safely Data infrastructure — ClickHouse analytics pipelines, real-time anomaly detection, and platform health monitoring (our "Radar" initiative) AI agent development — constrained, repeatable diagnosis agents that follow investigation playbooks, produce structured outputs, and operate with appropriate guardrails Knowledge engineering — building and curating the corpus that makes our AI tools accurate: documentation, training material, structured metadata, and feedback loops Internal tooling — full-stack applications that bridge the gap between data, AI, and the people who need answers What We Need Technical: Strong Python — your primary language for AI tooling, data pipelines, and backend services TypeScript / JavaScript — for Slack integrations, web interfaces, and full-stack tooling Go experience is a bonus — we use Go extensively for backend services and CLI tooling SQL — comfortable writing analytical queries against large datasets (ClickHouse, PostgreSQL, or similar) Familiarity with LLM APIs and tooling — Claude, OpenAI, or similar; prompt engineering, function calling, tool use Experience with Docker, Kubernetes, and AWS — your tools will run in production infrastructure Git and Linux fundamentals Experience in financial services is a plus but not essential — domain knowledge can be learned; engineering instinct cannot How you work: You ship. You're delivery-focused — you iterate quickly, you get things in front of users, you improve based on feedback You bridge domains. You're comfortable moving between AI, data, infrastructure, and product. You don't wait for someone else to define the interface — you go and understand the problem yourself You own it. When you build something, you take responsibility for its behaviour in production. You monitor it, you fix it, you make it better You write things down. Documentation is how we scale knowledge across a distributed team. Good documentation also makes our AI tools better — every well-written page becomes training material You communicate. We're a distributed team across multiple time zones. Clear, proactive communication is essential You embrace AI as a tool. You use AI to amplify your own productivity — and you build tools that do the same for others What You Get Greenfield AI work — you're not maintaining legacy systems; you're building the next generation of intelligent tooling for a trading platform Real impact — the tools you build will be used daily by engineers, operators, and eventually clients. This is not a side project An excellent team — senior engineers who care about craft, collaborate openly, and hold each other to high standards Ownership — small teams, clear accountability, direct impact on the platform and our people Competitive package — up to 30 days leave + bank holidays, private health insurance, pension, life insu