Manager, Software Engineering - Tax Platform

Intuit

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$237,500–$321,500 / yr
Posted
24 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $187k
This role $280k
$101k most similar roles pay here $345k

This role pays more than 90% of similar roles. Most pay $151,000–$222,625 — the shaded band above. At the midpoint, this role pays about $280k versus about $187k for comparable roles.

Based on 240 similar postings.

Employer

About Intuit

Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology

Intuit currently has 174 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 152 roles with salary data.

Most-posted roles

View all roles at Intuit

At a glance

TL;DR · Manager, Software Engineering - Tax Platform

Manager 3, Software Engineering - Tax Platform joins the Tax Platform organization to lead a large team of over thirty engineers and managers. This role focuses on overseeing tax engines, runtime platforms, and Tax Prep APIs while integrating Agentic AI capabilities into the core infrastructure. You will define multi-year technical roadmaps, manage engineering managers, and drive talent strategy including hiring and succession planning. Key responsibilities include ensuring system reliability, performance, and security for high-stakes tax computation systems while fostering an AI-native development culture. The role requires expertise in distributed systems, large-scale architecture, and operational excellence for business-critical systems. You will collaborate with product and design leaders to resolve cross-team friction and align technical priorities with customer impact. Preferred experience includes the tax domain or other highly regulated industries and familiarity with agentic AI tooling.

What does a Software Engineering Manager earn in California?

Median $281300 from 35 postings across 13 companies.

See salary data

What you'll do

  • Define the multi-year technical vision and roadmap for tax engines, runtime platforms, and Tax Prep APIs.
  • Manage, coach, and develop a team of engineering managers to build a durable leadership pipeline.
  • Integrate Agentic AI capabilities into the platform while maintaining strict compliance and accuracy standards.
  • Drive the adoption of GenAI tools and "paved roads" across all teams and development processes.
  • Oversee operational excellence for tax-critical systems, including reliability, incident response, and on-call health.
  • Align engineering priorities with product and design goals to resolve systemic cross-team friction points.
  • Manage talent strategy including hiring plans, succession planning, and performance calibration for managers and senior ICs.
  • Translate high-level company strategy into scalable execution systems across multiple teams and capabilities.

What we're looking for

  • 10+ years of software engineering experience.
  • 5+ years of people leadership experience, including a track record of managing other managers.
  • Experience leading engineering strategy across multiple teams or capability areas on a one- to three-year planning horizon.
  • Experience owning technical direction and architecture for complex, distributed systems or platforms at scale.
  • Track record of building leadership pipelines through hiring, developing, and retaining engineering managers and senior ICs.
  • Applied experience partnering with platform teams to drive AI/GenAI adoption and embedding AI into products and processes.
  • Experience owning operational excellence for business-critical, tier-1 systems.
  • Strong track record of cross-functional influence with Product, Design, and Program leadership.
  • Experience in the tax domain or another highly regulated industry (preferred).
  • Direct experience with agentic AI tooling or infrastructure (preferred).
  • Experience contributing to shared platforms used across an engineering organization (preferred).
  • Contributions to open source, patents, or industry engagement (preferred).

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