Tern

Tern

Staff Engineer, R&D AI Tooling

United States · Staff+

Sponsorship not specifiedDetected 47 days ago
RubyRailsCode ReviewPostgreSQLBigQueryGCPREST

About the role

  • AI adoption and fluency is demanded, and is world class across the entire org.
  • Nearly 98% of travel agencies are small businesses.
  • These businesses have been chronically underserved by technology.

Responsibilities

  • Accelerate and compound our R&D workflows: optimize day, to, day engineering, build and improve custom skills and agents, push toward fully agentic overnight workflows where they make sense
  • Public signal: You write or build in the open on agentic patterns, MCP, evals, or codegen. People in this space already follow your work. If we've heard of you and are following your work, we want to talk.
  • Leveling instinct: You're genuinely excited about bringing the team along, not just building ahead of everyone. Navigating that gap, with real excitement about it, is something you've done before.
  • Through every peak and valley, we lead with curiosity, laughter, kindness, and resolve.
  • We believe that compounding habits lead to sustainable productivity, consistency, and mutual trust.

Requirements

  • Experience with MCP server development or Claude Code integrations

Skills

  • Staff or principal background at an AI-native company that has genuinely figured out agentic workflows.

Compensation

  • Competitive salary, equity, and benefits package

Benefits

  • Competitive salary, equity, and benefits package
  • Whether you're deepening your craft, learning from a teammate, or embracing a new challenge, growth is core to our identity.

Company info

  • Treat teaching and building in the open as a primary part of the job, not a tax on it
  • At every level of the organization, we obsess about understanding those we serve and the industry we operate in.
  • Be part of a mission-driven team transforming the travel planning space

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