Coin Market Cap: Technical AI Product Manager

<p> <strong>Headquarters:</strong> Global / Dubai / Hong Kong / Singapore </p> <div class="content"><div class="section-wrapper page-full-width"><div class="section page-centered"><div><span>About the role</span></div><div><br></div><div><span>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 </span><a class="postings-link" href="http://feedback.Once"><span>feedback.Once</span></a><span> 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>What you’ll do</span></div><div><br></div><div><span>Includes but not limited to:</span></div><div><br></div><div><span>1. Identify the biggest user pain points where a crypto AI can materially improve outcomes.&nbsp;</span></div><div><span>2. Turn ambiguous ideas into a clear MVP, with crisp scope, constraints, and success metrics.</span></div><div><span>3. Prototype full AI experiences in Python to validate value and quality before we ship to production. </span></div><div><span>4. Own prompts and context engineering: instruction design, context shaping, guardrails, tool/function calling patterns, and output formatting.</span></div><div><span>5. Build practical evaluation loops: golden sets, scenario coverage, qualitative rubrics, regressions, and acceptance criteria.</span></div><div><span>6. Design the AI user experience: make it clear, trustworthy, and resilient if things go wrong.</span></div><div><span>7. Run fast experiments, learn from real outputs and usage data, and iterate quickly.</span></div><div><span>8. Partner with Engineering to ship: provide handoff specs, edge cases, evaluation results, and support debugging and iteration post-launch.</span></div><div><span>9. Work on whatever surface is the highest leverage.&nbsp;</span></div><div><br></div><div><span>What we’re looking for</span></div><div><br></div><div><a class="postings-link" href="http://1.Strong"><span>1.</span><span>Strong</span></a><span> product judgment and the ability to make good calls under ambiguity.</span></div><div><span>2. Hands-on Python prototyping ability: you move fast, write clean code, and can translate ideas into working prototypes.</span></div><div><span>3. Practical LLM experience + intuition: you understand prompt iteration, context design, and have a strong intuition for how to build useful products on top of LLMsA strong evaluation mindset: you can define quality, test for failure modes, and prevent regressions without heavy process.</span></div><div><span>4. High-agency execution: you can go from “vague problem” → “shipped learning” with minimal supervision.</span></div><div><span>5. Excellent communication skills (verbal and written): convey complex messages clearly and simply, and driving conviction across stakeholders.</span></div><div><br></div><div><span>Nice to have</span></div><div><br></div><div><a class="postings-link" href="http://1.Shipped"><span>1.</span><span>Shipped</span></a><span> user-facing AI features (chat, agents, copilots, summarization, search/Q&amp;A, personalization).</span></div><div><span>2. 0 to 1 experience in fast-moving environments and owning ambiguous problems end-to-end. </span></div><div><span>3. Experience building tool-using and agent-like workflows. </span></div><div><span>4. Experience and interest in cryptocurrency. </span></div><div><br></div><div><span>We have a strong preference for candidates who can point to things they’ve built (prototypes, side projects, or shipped features) and explain how they navigated ambiguity to reach a useful outcome. To stand out, include examples of these in your application.&nbsp;</span></div><div><br></div><div><br></div><div><br></div><div><br></div></div></div></div> <p><strong>To apply:</strong> <a href="https://weworkremotely.com/remote-jobs/coin-market-cap-technical-ai-product-manager">https://weworkremotely.com/remote-jobs/coin-market-cap-technical-ai-product-manager</a></p>