No information about remote work conditions has been provided for this job.
Type of contract for this position: Permanent contract
The position
Job description
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
Benefits
Tech: Choose your laptop and accessories of choice
Flexible Time Off: Take the time you need - we encourage our team to unplug with unlimited PTO
Compensation: Startup equity for full-time employees
Wellness: Top tier health insurance along for full-time employees
WFH Wednesday: A dedicated work from home day each week + additional flexibility by team!
Team: Retreats, happy hours, and events for our team, friends, and family
Food: All meals while working, plus snacks. We take our snacking seriously
Preferred experience
Strong product intuition. You identify customer problems that AI can uniquely solve and partner with Product to shape what gets built, not just how
Ability to drive technical alignment across teams. You’ll be defining primitives and patterns that other engineers build on, so you need to bring people along
7+ years of experience building production systems, with deep hands-on expertise in LLMs, agentic architectures, retrieval systems, and evaluation frameworks
Pragmatic engineering judgment: you know when to move fast and when to invest in quality
Founder mentality with bias toward action, ownership, and urgency; you’re energized by the challenge of bringing a new AI product to market
Proven track record leading 0→1 technical initiatives with high ambiguity, driving them from concept to production
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