Technical AI Product Manager at CoinMarketCap

<div><span style="font-size: 16pt;">About the role</span></div><div><br></div><div><span style="font-size: 11pt;">CoinMarketCap is building AI products to help users discover, understand, and act on crypto information more effectively. We’re hiring a Technical AI Product Manager to join our AI team. This is an individual contributor role in the Product org. You’ll spend most of your time building and iterating: identifying user pain points, prototyping in Python, prompt engineering, context engineering, and improving AI features we’ve already shipped based on real usage and feedback.Once an MVP is validated, you’ll partner with Engineering to productionize and scale it. You are not responsible for long-term platform scalability or owning the full engineering surface area. You are responsible for producing strong prototypes and handing Engineering a clear, validated direction.</span></div><div><br></div><div><span style="font-size: 16pt;">What you’ll do</span></div><div><br></div><div><span style="font-size: 11pt;">Includes but not limited to:</span></div><div><br></div><div><span style="font-size: 11pt;">1. Identify the biggest user pain points where a crypto AI can materially improve outcomes.&nbsp;</span></div><div><span style="font-size: 11pt;">2. Turn ambiguous ideas into a clear MVP, with crisp scope, constraints, and success metrics.</span></div><div><span style="font-size: 11pt;">3. Prototype full AI experiences in Python to validate value and quality before we ship to production. </span></div><div><span style="font-size: 11pt;">4. Own prompts and context engineering: instruction design, context shaping, guardrails, tool/function calling patterns, and output formatting.</span></div><div><span style="font-size: 11pt;">5. Build practical evaluation loops: golden sets, scenario coverage, qualitative rubrics, regressions, and acceptance criteria.</span></div><div><span style="font-size: 11pt;">6. Design the AI user experience: make it clear, trustworthy, and resilient if things go wrong.</span></div><div><span style="font-size: 11pt;">7. Run fast experiments, learn from real outputs and usage data, and iterate quickly.</span></div><div><span style="font-size: 11pt;">8. Partner with Engineering to ship: provide handoff specs, edge cases, evaluation results, and support debugging and iteration post-launch.</span></div><div><span style="font-size: 11pt;">9. Work on whatever surface is the highest leverage.&nbsp;</span></div><div><br></div><div><span style="font-size: 13pt;">What we’re looking for</span></div><div><br></div><div><span style="font-size: 13pt;">1.</span><span style="font-size: 11pt;">Strong product judgment and the ability to make good calls under ambiguity.</span></div><div><span style="font-size: 11pt;">2. Hands-on Python prototyping ability: you move fast, write clean code, and can translate ideas into working prototypes.</span></div><div><span style="font-size: 11pt;">3. Practical LLM experience + intuition: you understand promp