AI Forward Deployed Engineer
Bullish · Hong Kong · 1mo ago
About Bullish
Bullish is an institutionally focused global digital asset platform that provides market infrastructure and information services. These include:BullishExchange– 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.CoinDeskIndices– 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.CoinDeskData- a broad suite of digital assets market data and analytics, providing real-time insights into prices, trends, and market dynamics.CoinDeskInsights– a digital asset media and events provider and operator ofCoindesk.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 ProductAI 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 works at 3am when nobody's watching." Evals, error handling, observability. You've thought about this.
A process-driven mindset. You document how things work before someone asks you to. Your SOPs and checklists aren't overhead — they're how you stay sharp and move fast without dropping things.
You've always had ideas. Now you can ship them. AI coding agents removed the bottleneck that used to sit between your thinking and working software. You don't wait for an engineer to build what you've already figured out.
Communication that closes the gap. You can translate what you built into terms that matter to the business partner who asked for it.
Formal experience: 2+ years in a role where you shipped tools that people actually used.
Nice to Haves
Experience with vector databases (Qdrant, Pinecone, pgvector)
Familiarity with SQL and relational databases so you can pull your own data
Docker / containerization basics
Any exposure to blockchain or trading concepts (we'll teach you what you need)
As part of your application, please submit a short video introduction (5–10 minutes). Screen-share and walk us through an AI project you've built: what problem it solved, the decisions you made, and how it holds up in production.
Please record the video on your device and share an accessible Google Drive link containing the file (in MP4, WMV, or MOV format) within your submission. A Bullish talent acquisition team member will reach out to request access upon review.
Bullish is proud to be an equal opportunity employer. We are fast evolving and striving towards being a globally-diverse community. With integrity at our core, our success is driven by a talented team of individuals and the different perspectives they are encouraged to bring to work every day.