Drimva

Gallup

Staff Engineer — Product Engineering

$240K–$300K

San Francisco · Staff · Full-time · Posted Aug 31, 2026

Experience
At least eight years of professional software engineering experience; demonstrated impact at a staff or equivalent cross-team scope.
Education
Bachelor's degree in computer science, computer engineering or a related field, or equivalent experience.

About the job

Provides cross-team technical leadership and hands-on engineering across product initiatives, while shaping engineering practices, architecture, and the use of AI-assisted development.

What you'll do

  • Advise the head of engineering and guide teams on architecture and technical direction across concurrent initiatives.
  • Promote effective AI-assisted engineering, mentor senior engineers and tech leads, and establish shared technical practices.
  • Evaluate emerging tools and patterns, shape product priorities using data, and contribute hands-on to critical initiatives.

What they ask for

  • Bachelor's degree in computer science, computer engineering or a related field, or equivalent experience.
  • At least eight years of professional software engineering experience, with demonstrated impact at a staff or equivalent cross-team scope.
  • Track record of influencing technical direction across teams without direct management authority; experience mentoring senior engineers and technical leads.
  • Hands-on production experience with AI-assisted development tools; strong system design and architecture fundamentals.
  • Commitment to working on-site at Gallup’s San Francisco office at least three days per week.

Nice to have

  • Experience partnering with an engineering leader in an advisory, thought-partner capacity.
  • Experience with identity and access platforms (such as Auth0 or Okta), survey or assessment-driven products, or large-scale platform migrations.

Pay

$240,000-$300,000 USD annual salary

Tools

AI-assisted development tools, Auth0, Okta

AI focus

Set standards for AI-assisted engineering, apply AI tools where they improve speed, and partner on governance and best practices while maintaining human judgment.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 5, 2026 (UTC)