AI Forward Deployed Engineer at Bullish

About Bullish Bullish is an institutionally focused global digital asset platform that provides market infrastructure and information services. These include: Bullish Exchange – a regulated and institutionally focused digital assets spot and derivatives exchange, integrating a high-performance central limit order book matching engine with automated market making to provide deep and predictable liquidity. Bullish Exchange is regulated in Germany, Hong Kong, and Gibraltar. CoinDesk Indices – a collection of tradable proprietary and single-asset benchmarks and indices that track the performance of digital assets for global institutions in the digital assets and traditional finance industries. CoinDesk Data - a broad suite of digital assets market data and analytics, providing real-time insights into prices, trends, and market dynamics. CoinDesk Insights – a digital asset media and events provider and operator of Coindesk.com , a digital media platform that covers news and insights about digital assets, the underlying markets, policy, and blockchain technology. Reports to: Product Manager - Exchange Product AI Engineer — Internal Tools & Automation The AI Engineering team acts as an internal catalyst. We identify where the business is slow, build tools to fix it, and move on. Our work spans Customer Success, Exchange Operations, Trading, and Custody — wherever there's friction worth eliminating. This isn't a research role. We ship fast, measure impact, and iterate. You'll spend more time prototyping with LLMs and building agentic workflows than writing infrastructure, but you'll own what you build all the way to production. What You'll Do Partner with a business counterpart to identify and scope operational bottlenecks, then build the tools to fix them Move autonomously across the organization: gather requirements, secure data access, and earn the trust of teams you're helping Ship quickly using whatever fits: n8n, Make, Zapier, Lovable, or custom Python. Right tool for the right job. Build and maintain production AI systems: RAG pipelines, conversational interfaces, workflow automation, internal agents Run workshops and training sessions to help non-technical teams actually use what you build Define metrics upfront, track them, and tell the story of what changed What We're Looking For We care more about what you've shipped than where you worked. Show us: A portfolio of things you've built. Personal projects, side tools, public demos, anything you can point at. GitHub, a writeup, a Loom walkthrough, a live URL. All count. Evidence you move fast with LLMs. You've run multiple coding agents in parallel and know how to coordinate between them. You have a feel for how capable frontier models actually are, and you match model intelligence to task complexity rather than defaulting to the biggest one every time. Production instincts. You've dealt with the gap between "it works in the demo" and "it