Paveposted 18 days ago
Full-time • Mid Level
NY

About the position

At Pave, we're combining the world's largest real-time compensation dataset with deep expertise in AI and Machine Learning to reimagine how our clients make compensation decisions. By building the operating system for compensation, we're perfecting the art and science of pay to give 8,500+ companies unparalleled confidence in every compensation decision. Our engineering team moves between ideation, scoping, and execution in a matter of days while closely iterating with cross-functional partners on requirements. We're seeking passionate engineers who are excited about building robust, data-rich systems that simplify complex compensation processes at scale.

Responsibilities

  • Build performant, data-rich interfaces that handle complex logic and large datasets gracefully.
  • Collaborate with product managers, designers, and fellow engineers to deliver value to users.
  • Guide technical decisions based on customer needs and prioritize fast iteration versus robust architecture.
  • Thrive in fast-paced environments and ship thoughtful solutions without overengineering.
  • Adapt to ambiguity and validate direction through prototypes.

Requirements

  • 5+ years of frontend engineering experience, ideally using modern web technologies such as TypeScript and Node.js.
  • At least 2 years building data-intensive applications.
  • Strong data visualization expertise.
  • Strong product intuition.
  • Execution-driven mindset.
  • Collaborative working style.

Nice-to-haves

  • Experience at B2B SaaS companies, especially during periods of rapid growth or platform expansion.

Benefits

  • Comprehensive Medical, Dental and vision coverage for you and your family.
  • Flexible PTO and the ability to work from anywhere in the world for a month.
  • Lunch & dinner stipends as well as fully stocked kitchens.
  • Quarterly education stipend to continuously grow.
  • Robust parental leave to bond with your new family.
  • A commuter stipend to help you collaborate in person.
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