Pace

Pace

Member of Technical Staff

New York, NY · Staff+

Sponsorship not specifiedDetected 26 days ago
Full-Stack DevelopmentAgentic AILeadership

About the role

  • Pace is an AI-native business process outsourcer for insurers.
  • We combine the speed of AI agents with expert review by our insurance operations team to automate insurance tasks.
  • We're here to change that working side-by-side with some of the largest companies in the world.

Responsibilities

  • 1) Backend engineer to own our extraction pipelines, 2) Full-stack engineer to own RPA/web automation features, 3) Enterprise engineer to work with our largest users building features that make them successful as they scale.
  • Our team genuinely wants to do the best work of their careers and know it'll take 5-10 years of focus to deliver.
  • Often times this means they want to be the best at what they do, become leaders at scale or one day start their own company.
  • Pace will be the best place to learn, deliver impact and advance your path to do something great.
  • You'll be leading the company not just in engineering but across many potential paths: → Engineering leadership → GM of a business line We want to support you to grow at Pace and beyond for the long-term.

Compensation

  • Pace is an AI-native business process outsourcer for insurers.
  • We combine the speed of AI agents with expert review by our insurance operations team to automate insurance tasks.
  • Almost $400bn per year is spent on outsourcing in financial services every year.
  • We're here to change that working side-by-side with some of the largest companies in the world.
  • Role We're looking for a Member of Technical Staff who will partner with our team on product.

Company info

  • We're looking for people that raise that level of ambition.
  • We're lucky to be perfectly positioned with leading customers and top investors to make a real impact on one of the largest industries in the world.

This listing is sourced directly from Pace's careers page and normalized into a canonical job model.