Senior Compensation Strategy & Systems Manager, Replit

• 8+ years in compensation, total rewards, or related analytical roles — ideally at a high-growth tech company
• Deep expertise in salary bands, equity design, and market benchmarking (broad-based, sales, and executive)
• Strong systems thinker who can translate policy into scalable workflows and decision logic
• Product mindset — you think in terms of users, workflows, and iteration
• Comfortable partnering with Data/Engineering teams on data architecture and internal tooling
• High ownership; willing to operate hands-on

Desirable

• Replit is the world's most widely used AI coding platform, and as we scale, we're rebuilding how compensation works internally from the ground up
• This role owns that. You'll go beyond traditional comp management to architect the systems, data infrastructure, and AI-enabled workflows that make fast, consistent, and high-quality compensation decisions possible at scale
• It's a rare opportunity to bring a product and engineering mindset to a people function that most companies still run on spreadsheets
• You will serve as the architect of our compensation engine: translating compensation philosophy into scalable systems, and leveraging data, automation, and AI to improve speed, accuracy, and transparency
• This role sits at the intersection of compensation, product, and systems design
• You will partner closely with People Business Partners, Recruiting, Finance, People Operations, and the Data team to embed compensation directly into company workflows—eliminating manual processes and reducing reliance on comp as a service layer
• You will shape how we attract, reward, and retain top talent, while building infrastructure that scales with the business
• Compensation Strategy:
• Evolve our compensation philosophy across cash and equity; design and maintain salary bands, leveling frameworks, and equity structures
• Ensure market competitiveness while partnering with Finance on cost and workforce planning
• Systems & Data Architecture:
• Partner with Data Science to define compensation data schemas, pipeline requirements, and unified data models that allow AI agents and internal tools to query compensation data seamlessly
• Own the compensation tech stack : build vs. buy decisions, HRIS/ATS/equity platform integrations, and security/permissioning standards
• AI-Native Workflows:
• Design and implement AI-enabled workflows for offers, merit, promotions, and market adjustments
• Build human-in-the-loop validation frameworks to audit AI-generated recommendations for bias, accuracy, and logic
• Decision Support & Analytics:
• Operate compensation planning cycles and generate first-pass recommendations for comp decisions
• Build dashboards and analytical frameworks covering market competitiveness, internal equity, retention risk, and workforce cost
• Tools: Pave, Radford, Rippling, Lattice, Ashby, Carta, Google Sheets, internal AI/automation tooling