Senior Product Manager

Senior Product Manager
Product Management | Reports to VP, Product Management

About the role

You own a new product build from ambiguity to a shipped, adopted product, and you lead the small team that builds it. This is an insurtech role, so the domain matters. You should already know how agencies and brokerages actually work and what makes insurance workflows hard.

You will also lead a team of product owners and product builders. That means setting the bar for spec quality, reviewing their work, developing them, and stepping in on the hardest problems yourself. You are close enough to the work to write a spec or prototype, not just review one.

What you will do

• Own a new product from problem definition through launch and early adoption. Decide what gets built, in what order, and when to stop.
• Lead and develop a team of product owners or product builders. Set expectations, give direct feedback, and raise the quality of what the team produces.
• Sit with agency users directly. Interviews, usability sessions, win and loss. Turn what you hear into problem statements with evidence behind them.
• Write specs with clear scope boundaries and testable acceptance criteria that both the team and an AI agent can work from.
• Define what correct means, including how AI assisted output gets verified before customers see it.
• Set success metrics before work starts and report against them after launch.
• Partner with engineering, design, sales, and marketing through build and go to market.

Requirements

• 5+ years in product management, including 3+ years in insurtech or insurance software.
• Experience leading or mentoring other product people. Formal management experience preferred, but a strong track record of raising the bar for a team counts.
• Experience taking a new product or major new capability from zero to launch, not just running an existing roadmap.
• Experience taking an AI solution from zero to launch
• 12+ months of hands-on daily use of AI tools in your product work: specs, research, prototyping, analysis. Practical fluency, not a research background.
• Exposure to an AI assisted development lifecycle. Specs written for agent execution, human review gates, evals that define correctness. Exposure and curiosity clear the bar.
• Comfortable working directly with customers and directly with engineers.