Senior Software Engineer - Core Platform

Senior Software Engineer - Core Platform

Who We Are

At Pave, we're building the industry’s leading compensation platform, combining the world's largest real-time compensation dataset with deep expertise in AI and machine learning. Our platform is perfecting the art and science of pay to give 8,500+ companies unparalleled confidence in every compensation decision.

Top tier companies like OpenAI, McDonald’s, Instacart, Atlassian, Synopsys, Stripe, Databricks, and Waymo use Pave, transforming every pay decision into a competitive advantage. $190+ billion in total compensation spend is managed in our workflows, and 58% of Forbes AI 50 use Pave to benchmark compensation.

The future of pay is real-time & predictive, and we’re making it happen right now. We’ve raised $160M in funding from leading investors like Andreessen Horowitz, Index Ventures, Y Combinator, Bessemer Venture Partners, and Craft Ventures.

Research & Development

The R&D organization encompasses engineering, product, design, data science, and security. We’re a high performing team that moves between ideation, scoping, and execution in a matter of days. Everyone on the team has high agency to design, experiment, and build great software in partnership with our pre-sales and post-sales teams, and our clients.

We're seeking passionate engineers who are excited about building robust, data-rich systems that simplify complex compensation processes at scale. Our stack is React, TypeScript, Node.js, MySQL, and BigQuery hosted on GCP.

Core Platform @ Pave

The Core Platform team sits at the center of Pave Engineering, bridging product and platform engineering. We build the foundational services, APIs, and abstractions that enable every team to ship enterprise-grade software with speed and confidence. In this role, you’ll own critical services like user authentication and authorization, as well as the foundational data infrastructure and models powering Pave’s compensation intelligence platform. Success in this role requires strong systems thinking and the ability to drive large, complex initiatives across the organization.

What You''ll Bring

• 5+ years of backend engineering experience building data intensive applications, ideally utilizing modern web technologies such as TypeScript and Node.js
• Strong product intuition with the ability to design generalized platform solutions that solve cross-product challenges
• Hands-on experience with data infrastructure, data pipelines / ETLs, data modeling; ML / AI platform experience a plus
• Experience leading large technical projects with high ambiguity and numerous stakeholders
• Execution-oriented. You thrive in fast-paced environments and bias toward action

Compensation, It''s What We Do.

Salary is just one component of Pave's total compensation package for employees. Your total rewards package at Pave will include equity, top-notch medical, dental, and vision coverage, an unlimited PTO policy, and many other region-specific benefits. Your level is based on our assessment of your interview performance and experience, which you can always ask the hiring manager about to understand in more detail.

Salary Range for this role : $195,500 - $264,500

Life @ Pave

Since being founded in 2019, Pave has established a robust global footprint. Headquartered in San Francisco's Financial District, we operate strategic regional hubs across New York City's Flatiron District, Salt Lake City, and the United Kingdom. We cultivate a vibrant, collaborative workplace culture through our hybrid model, bringing teams together in-person on Mondays, Tuesdays, and Fridays to foster innovation and strengthen professional relationships

Benefits @ Pave

At Pave, career advancement drives everything—roles expand, responsibilities deepen, and compensation rises alongside your professional growth.

What we provide

Vision

Our vision is to unlock a labor market built on trust

Mission

Our team's mission is to build confidence in every compensation decision

Are you ready to help our clients make smarter, more effective compensation decisions?

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