Drimva

Gusto

Senior Staff Engineer - Tax Platform Engineering

$189K–$278K

Atlanta, GA - Hybrid +9 · Remote · Senior Staff · Full-time · Posted Jul 2, 2026

Location
Atlanta, GA - Hybrid
Austin, TX - Remote
Chicago, IL - Remote
Denver, CO - Hybrid
Los Angeles, CA - Remote
Miami, FL - Remote
New York, NY - Hybrid
San Francisco, CA - Hybrid
Seattle, WA - Remote
San Francisco, CA - Hybrid
Experience
At least 10+ years of experience.

About the job

Design and lead scalable tax-platform systems that support payroll tax compliance, reliable operations, and safe use of AI in tax workflows.

What you'll do

  • Own technical strategy and roadmap; guide projects across teams and prioritize foundational architecture investments.
  • Design, build, and test tax-compliance platform capabilities, improving scalability, reliability, and incident response.
  • Build platform guardrails for compliant, accurate, and reliable agentic AI use; mentor engineers and improve team productivity.

What they ask for

  • Experience designing and developing robust distributed systems using multiple general-purpose programming languages.
  • Experience influencing multiple teams on scaling, refactoring, and optimizing legacy products.
  • Experience architecting, building, and testing large-scale production-level code, including fault-tolerant, mission-critical software.
  • Experience building products in highly regulated, high-risk domains; familiarity with current AI tools and their benefits and shortcomings.

Nice to have

  • Experience in Payroll, Taxes, or Compliance.
  • Experience with Ruby on Rails, Typescript, and React.

Pay

$189,000–$236,000 per year (base salary) in Denver and most remote locations; $223,000–$278,000 per year (base salary) in San Francisco and New York.

Tools

Ruby/Rails, TypeScript/React, LLMs, Agents

AI focus

Build guardrails for safe, compliant, accurate, stable, and reliable agentic AI interaction with tax concepts; use AI tools in daily development to reduce cycle time; mentor engineers in AI usage and help develop AI strategy.

Model-written summary · the original posting is authoritative

First seen Oct 10, 2026 · Last verified Nov 5, 2026 (UTC)