SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Legora is an AI-native legal workspace trusted by 1,000+ customers globally, including top-tier law firms and enterprises. The company has scaled to $100M+ ARR and operates across Europe, North America, and APAC.
As Total Rewards Manager, you will lead Legora's compensation architecture and equity programs, reporting to the VP of Total Rewards. This is a strategic builder role focused on translating reward strategy into scalable systems as the company grows across multiple markets.
Key responsibilities include:
- Defining and maintaining compensation bands across job architecture, ensuring consistent application and market alignment across functions and geographies
- Leading the annual compensation review cycle end-to-end: benchmarking, calibration, offer modeling, and manager communication
- Serving as the company's expert on equity programs, including plan structures, grant cycles, vesting, and integration with total reward strategy
- Implementing and evolving compensation frameworks and total reward practices aligned with global strategy while ensuring competitiveness, equity, and transparency
- Conducting ongoing market benchmarking across all markets to keep Legora competitive
- Partnering with Finance on compensation planning, equity modeling, and reward analytics
- Collaborating with Legal to ensure compliance across all jurisdictions
- Building scalable toolkits, templates, and policies for consistent reward decisions
- Educating managers and employees on reward philosophy and practices
You bring 7+ years of compensation and total rewards experience, ideally in high-growth tech or scale-up environments. You have strong expertise in compensation banding and benchmarking, solid understanding of equity programs, strong analytical skills, and a proven track record partnering with Finance and Legal. You excel at translating complex reward topics into clear language for diverse audiences and think systematically about how data, structure, and people intersect.