Engineering Lead

Hex Hex · Data AI · United States · Engineering

Engineering Lead to drive strategy, execution, and growth of Hex’s AI context platform, focusing on how AI agents interact with data, improve system intelligence, and manage business context. The role involves leading a team, defining technical strategy, and hands-on contributions to building and improving AI agent behavior and context systems.

What you'd actually do

  1. Lead a team working on Hex’s context platform
  2. Drive technical strategy, review designs, and directly contribute with hands-on work
  3. Serve as people manager for the engineers on the team, setting a high bar and empowering them to do their best work
  4. Recruit exceptional engineering talent

Skills

Required

  • 4+ years of experience as a full-stack software engineer
  • 2+ years experience leading engineering teams working on complex, data-intensive, or AI-driven products and SaaS platforms
  • people management
  • technical strategy
  • designing technical abstractions
  • building and operating product engineering teams
  • setting clear technical standards
  • hiring and developing strong talent

Nice to have

  • Deep curiosity for, and strong intuition about, state-of-the-art AI agent behavior and context systems

What the JD emphasized

  • state-of-the-art AI context platform
  • AI agents interact with their data
  • improve the intelligence of our system
  • detect and debug failures in agent reasoning
  • structure and manage business context effectively
  • balance human-in-the-loop systems with autonomous improvement
  • integrate our context layer with the growing ecosystem of AI-powered tools and workflows
  • 4+ years of experience as a full-stack software engineer
  • 2+ years experience leading engineering teams working on complex, data-intensive, or AI-driven products and SaaS platforms
  • Proven track record as a people manager
  • clear playbook for building high-performing teams
  • Deeply technical leader who is not afraid to roll up your sleeves and get hands-on when necessary

Other signals

  • AI context platform
  • AI agents interact with data
  • improve the intelligence of our system
  • detect and debug failures in agent reasoning
  • structure and manage business context effectively
  • balance human-in-the-loop systems with autonomous improvement
  • integrate our context layer with AI-powered tools and workflows