Staff Software Engineer

Intuit

Confirmed live today High trust

Quick summary

Work type
On-site
Location
New York, NY
Salary
$202,500–$274,000 / yr
Posted
77 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $228k
This role $238k
$175k $285k
below market most similar roles pay here above market

This role pays more than 67% of similar roles. Most pay $200,762–$254,750 — the blue band above. At the midpoint, this role pays about $238k versus about $228k 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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View all roles at Intuit

At a glance

TL;DR · Staff Software Engineer

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 architect production-grade systems designed for scalability, security, and compliance while leading technical designs that influence industry standards. Daily responsibilities include managing cross-system risks, collaborating with domain and compliance stakeholders, and mentoring engineers. Required skills include expertise in distributed systems, agent-driven development, and frontier fintech infrastructure like payments or identity systems. You must be fluent in Java, Python, JavaScript, TypeScript, React, Node, and Kubernetes-based runtimes like AWS EKS. The work focuses on enabling autonomous AI agents to initiate and settle transactions using a cross-asset financial graph.

What does a Software Engineer earn in New York?

Median $216000 from 270 postings across 57 companies.

See salary data

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 a 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, scaling, and deployment patterns.
  • Review code and set technical direction across a polyglot engineering team using Java, Python, and TypeScript.

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 a frontier fintech infrastructure area such as 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, scaling, and deployment 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 on-device inference pipelines (preferred).

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