AI Engineer - Paige
PaveSan Francisco, CA & New York, NYPosted 20 February 2026
Job Description
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 70% 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.
The Paige Team @ Pave
Paige is Pave's AI compensation analyst - an agentic system that sits on top of the world's largest proprietary compensation dataset and Pave's existing workflow engine. Think: autonomous agents that can reason over structured compensation data and execute multi-step workflows (market pricing, cycle planning, attrition analysis) across Pave's platform. In this role, you'll shape the technical vision and execution of Paige, working with a team of engineers and data scientists to build the product end-to-end and take it to market. This role requires deep AI expertise, strong product intuition, and a founder mentality.
What You'll Bring
3+ years building production systems, with hands-on experience working with LLMs, agentic architectures, and retrieval systems
Strong product instincts. You want to understand the customer problem and why it matters
Experience shipping features end-to-end in ambiguous, fast-moving environments
Pragmatic engineering judgment: you know when to move fast and when to invest in quality
Collaborative by default. You communicate clearly, work well across teams, and leave codebases better than you found them
High agency with bias toward action and ownership; you're energized by the challenge of bringing a new AI product to market
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. This salary range may include multiple levels.
The targeted cash compensation for this position is (level depends on experience and performance in the interview process):
P3: $166,600 - $225,400
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, Thursdays, 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
Complete Health Coverage : Comprehensive Medical, Dental and Vision coverage for you and your family, with plenty of options to suit your needs
Time off Flexibility : Flexible PTO and the ability to work from anywhere in the world for a month
Meals Snacks : Lunch dinner stipends as well as fully stocked kitchens to fuel you
Professional Development : Quarterly education stipend to continuously grow
Family Support : Robust parental leave to bond with your new family
Commuter Assistance : A commuter st ... (truncated, view full listing at source)
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