Staff Software Engineer

Intuit

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Mountain View, CA
Salary
$202,500–$274,000 / yr
Posted
2 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $226k
This role $238k
$175k $285k
below market most similar roles pay here above market

This role pays more than 69% of similar roles. Most pay $198,790–$252,237 — the blue band above. At the midpoint, this role pays about $238k versus about $226k 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 255 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 236 roles with salary data.

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At a glance

TL;DR · Staff Software Engineer

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The Fintech Futures - Staff Software Engineer joins a specialized engineering team defining next-generation fintech integration protocols. This role involves owning the technical vision for major capabilities, including agent-initiated settlement, edge AI-driven on-device financial agents, and portable verifiable trust. You will lead technical designs, architect complex distributed systems, and manage cross-system risks while acting as connective tissue between engineering and compliance stakeholders. The work focuses on building production-grade architecture that handles real transaction volume and maintains security and observability. Required skills include 8+ years of software development experience, fluency in Java, Python, JavaScript, TypeScript, React, and Node, and expertise in Kubernetes-based runtimes like AWS EKS. You must demonstrate proficiency in agent-driven development and frontier fintech infrastructure areas like payments, settlement, or identity systems.

What does a Software Engineer earn in California?

Median $214500 from 1157 postings across 75 companies.

See salary data

Skills

Java Python JavaScript TypeScript React Kubernetes AWS EKS Distributed Systems Edge AI Cloud-Native Model Compression On-device Inference Fintech Infrastructure Observability

What you'll do

  • Own the technical vision for major capabilities like agent-initiated settlement, edge AI, or verifiable trust.
  • Lead technical designs that position Intuit's engineering work as credible input for industry standards.
  • Anticipate and manage cross-system risks and dependencies across the entire product portfolio.
  • Translate technical proof points into scalable product requirements for domain and compliance stakeholders.
  • Champion strategic investments in frontier technologies to shape the team's technical roadmap.
  • Architect systems for agentic observability and reliable autonomous code navigation.
  • Make design decisions for Kubernetes-based runtimes including service topology and scaling patterns.
  • Review code and set technical direction across a polyglot engineering stack.

What we're looking for

  • 8+ years of experience developing software for large-scale business environments.
  • 5+ years of experience designing complex distributed systems.
  • BS/MS in Computer Science or a related field, or equivalent practical experience.
  • Demonstrated ownership of a complex technical domain end-to-end with a track record of setting technical direction.
  • Proven fluency in agent-driven development, including architecting for agentic observability and autonomous code navigation.
  • Deep expertise in payments/settlement, edge AI, or identity/trust systems.
  • Fluency in Java, Python, and JavaScript/TypeScript with React/Node to set technical direction and review code.
  • Fluency in making design decisions on Kubernetes-based runtimes, including service topology and scaling patterns.
  • Prior involvement in an open standards body or protocol working group (preferred).
  • Experience taking new technical capabilities through compliance/legal review to a beta or sandbox release (preferred).
  • Hands-on edge AI/on-device deployment experience, including model compression and inference pipelines (preferred).

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