Product Manager

Summary

Harper is an innovative company in the commercial insurance sector, leveraging AI to transform the distribution of insurance for small businesses. The Product Manager will own a module within the company's AI-driven processes, focusing on improving customer experience and operational workflows while ensuring effective measurement and evaluation of performance metrics.

Responsibilities

• Own the KPIs — Conversion, handle time, accuracy, autonomous resolution rate, retention—whatever the leverage point is for your surface. You set the targets, instrument them, move them. If the metric isn't moving, that's your problem
• Encode the nuance — Every module has industry-by-industry, segment-by-segment behavior to encode. You translate what makes your module's customers different into rules, prompts, agents, and data structures
• Own the eval regime — Probabilistic systems are only valuable when humans trust them. Regressions on every change, evals that map to real outcomes (not vibes), backtests against historical applications, call-by-call review where it matters. You'll be paranoid about silent regressions in a way most PMs aren't
• Build the data flywheel — Work hand-in-glove with data labeling and validation to build the golden datasets your module's models need. You define what "right" looks like so we can train, evaluate, and improve against a real bar
• Own the cross-modal experience — Your module spans web, voice, and human. You decide where each modality wins, where they hand off, and how the on-ramps feel
• Live with operators — Sit with sales, service, underwriting. Watch the work. Find what's broken before they tell you
• Talk to customers every day — Literally. Not "5 calls last quarter."
• Prototype with AI — Claude Code, Cursor, Lovable. Walk into the meeting with a working prototype, not a deck
• Hyper-prioritize — Out of 50 things people are asking your module to do, find the 3 that move the KPI and ignore the rest with conviction

Skills

• 1–3 years into product, OR an early-career operator, engineer, or AI researcher who's been doing the work without the title
• Demonstrated ownership of a product or system end-to-end—KPIs, roadmap, execution
• Proficiency using AI tools to prototype (Claude Code, Cursor, Lovable, or similar)
• Strong analytical instincts—you can argue tradeoffs with engineers on AI systems
• Track record of going deep on a domain and encoding what you learned into a system
• Based in San Francisco or willing to relocate
• Background in AI/ML products, voice AI, agent frameworks, or workflow automation
• Experience with eval design, prompt engineering, or context engineering
• Insurance, fintech, or regulated industry experience
• Prior startup experience

Qualifications

Must Haves

• 1–3 years into product, OR an early-career operator, engineer, or AI researcher who's been doing the work without the title
• Demonstrated ownership of a product or system end-to-end—KPIs, roadmap, execution
• Proficiency using AI tools to prototype (Claude Code, Cursor, Lovable, or similar)
• Strong analytical instincts—you can argue tradeoffs with engineers on AI systems
• Track record of going deep on a domain and encoding what you learned into a system
• Based in San Francisco or willing to relocate

Nice to Haves

• Background in AI/ML products, voice AI, agent frameworks, or workflow automation
• Experience with eval design, prompt engineering, or context engineering
• Insurance, fintech, or regulated industry experience
• Prior startup experience

Benefits

• Performance bonuses & equity
• Health, dental, and vision insurance
• Commuter benefits
• Team meals and snacks