Job Description & Details
This is a hands-on Product Manager role focused squarely on building and scaling agentic AI workflows and orchestration tools for enterprise merchants. If you like sitting right at the intersection of heavy data science, UX, and business strategy without getting bogged down in corporate red tape, this gig is worth a serious look.
What You'll Actually Be Doing
Your day-to-day will involve translating complex business processes into seamless agentic experiences while keeping a close eye on security and user trust. You'll spend a lot of time defining AI-powered workflow use cases, coordinating directly with engineering and data science teams, and building out rigorous agent evaluation frameworks. Expect to get your hands dirty with rapid prototyping tools to validate prompts and workflows before they ever hit production.
The Core Tech Stack
You need a strong grasp of LLM orchestration, prompt engineering iteration cycles, and agent evaluation frameworks like confidence scoring metrics. The team relies heavily on your ability to implement enterprise AI governance mechanisms—think human-in-the-loop review processes and audit trails—so you must understand the security and compliance constraints that come with deploying AI at an enterprise scale.
Interview Expectations
Expect the hiring manager to press you on how you handle accuracy drift and prompt iteration in production systems; they want to hear a structured approach to building confidence scoring metrics rather than just relying on vibes. They'll also likely ask you to walk through a time you balanced extreme flexibility for end-users with rigid security compliance, so have a concrete architectural or product trade-off story ready to go.
Application Advice
Make sure your resume leans hard into specific AI keywords like agentic workflows, prompt iteration, enterprise governance, and human-in-the-loop frameworks. Don't just list generic agile product management duties; highlight real metrics where you drove technical execution alongside data science and engineering teams to get an AI product across the finish line.