Agent Product Manager (AI)

Location: Boston or San Francisco, United States

Salary: $160,000–$235,000 per year, depending on level, experience, and location.

Company

Builds insurance-native AI agents that manage customer interactions across voice, SMS, email, and digital channels and execute downstream work in systems such as Guidewire, Duck Creek, Applied Epic, and Salesforce.

What you will do

• Own ambiguous enterprise customer problems from initial framing through measurable in-production outcomes.
• Lead executive-level customer engagements, communicate clearly under pressure, and establish realistic delivery plans.
• Use structured analytical methods to segment problems, quantify impact, prioritize work, and make decisions under ambiguity.
• Partner with Engineering on requirements, launch-critical tradeoffs, reusable platform capabilities, speed, quality, and scalability.
• Drive delivery, customer adoption, and measurable value beyond successful deployment.
• Turn recurring implementation solutions into reusable product, platform, playbook, or process improvements.

Requirements

• 6+ years of professional experience, including 3+ years in management consulting.
• Strong academic record and clear analytical strengths.
• Proven ownership of enterprise customer outcomes and complex implementations from start to finish.
• Exceptional structured thinking and communication skills, including the ability to explain complex work simply.
• High agency and comfort operating with ambiguity, competing constraints, and incomplete information.
• Evidence of a clear upward trajectory and raising the bar without being asked.

Nice to have

• Experience with AI/ML systems, workflow automation, or agent-based products.
• Background in insurance, fintech, or other regulated industries.
• Familiarity with system design tradeoffs and technical architecture.
• Experience productizing implementation solutions or creating reusable patterns.

Culture & Benefits

• Fast-paced, hands-on, customer-facing product ownership.
• Emphasis on building and operating solutions rather than only providing recommendations.
• Focus on production depth, regulated workflows, governance, and trust.
• Work involves close partnership with Engineering and enterprise customer leadership.