Hybrid Product Manager

at Reinforce Labs

• Job title: Product Manager
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: $130,000 - $160,000 per year
• Degree requirement: Bachelor's Degree
• Location requirements: Hybrid, Palo Alto, United States

About the role

• Product Manager overseeing customer-facing dashboards and metrics evaluation for an AI-powered SaaS startup. Collaborating with engineering for data-driven product decisions and user experience enhancements.

Responsibilities

• Own Metrics & Evaluation Frameworks: Define and evolve the core Metrics framework for AI readiness, safety, security, and compliance.
• Partner with ML/eng to design metrics and evaluation loops that reflect real-world risk.
• Work with GTM and customers to ensure metrics map cleanly to business outcomes and internal reporting needs.
• Build Customer Dashboards & UX: Own the end-to-end UX for customer-facing dashboards: readiness scores, risk heatmaps, experiment views, trend charts, and drill-downs into specific conversations.
• Translate complex technical signals (attack success rates, severities, false positives/negatives) into simple visualizations and narratives.
• Work closely with design to define information architecture, layouts, and interaction patterns.
• Drive Customer Discovery & Feedback Loops: Run customer discovery with T&S leaders, PMs, compliance, and security stakeholders to understand how they make decisions and what data they trust.
• Turn feedback and usage data into a prioritized roadmap for dashboards, reports, and self-serve analytics.
• Experimentation & Data-Driven Decisions: Define success metrics and guardrail metrics for new features; partner with eng/ML on rollouts.
• Use product analytics and customer data to understand adoption, engagement, and impact of dashboards and reports.

Requirements

• 4–8+ years of Product Management experience in B2B SaaS and/or AI/ML-powered products.
• Demonstrated experience owning customer-facing dashboards, analytics products, or reporting surfaces.
• High comfort with metrics: defining KPIs, reasoning about tradeoffs, and turning raw data into clear definitions and thresholds.
• Strong collaboration with engineering, ops, and data/ML teams
• Excellent written and verbal communication; you can explain complex AI risk concepts in simple language to non-technical stakeholders.
• Experience with LLMs, GenAI, or ML-based products
• Background working with trust & safety, security, compliance, or risk teams.
• Prior startup experience building v1 products and iterating quickly with design partners.

Benefits

• Offers Equity
• Offers Bonus