# Senior Compensation Strategy & Systems Manager

**Company:** [Replit](https://hotfix.jobs/companies/replit)
**Location:** Foster City, CA
**Role:** People Ops
**Salary:** $171k – $250k/yr
**Experience:** 8+ years
**Skills:** Pave, Radford, Rippling, Lattice, Ashby, Carta, Google Sheets, Salary Bands, Equity Design, Market Benchmarking
**Posted:** 2026-06-09

> Architect compensation systems and AI-enabled workflows at a high-growth AI coding platform. Own salary bands, equity structures, data architecture, and automation for offers, merit, and promotions.

## Job Description

## Compensation Strategy
- Evolve 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
- Enable 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

## Requirements
- 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 — 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

## Nice to Have
- Experience at an AI-native company
- Prior internal tools or engineering-adjacent work

## Tools
Pave, Radford, Rippling, Lattice, Ashby, Carta, Google Sheets, internal AI/automation tooling

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