Job description

We’re seeking a Principal Software Engineer to shape how AI transforms everyday work at Intuit. You will lead the technical strategy and engineering of shared capabilities that help employees find trusted information, make informed decisions, and complete complex workflows through collaboration with AI agents. As a senior individual contributor, you will turn ambiguous business problems into reliable production systems. Your scope will span the shared platform and a prioritized portfolio of employee workflows, connecting enterprise knowledge, business applications, and AI capabilities. You will remain hands-on with critical implementations while guiding architecture and engineering decisions across teams Responsibilities • Define the technical direction. Establish a multiyear architecture and roadmap for AI-powered work. Make clear decisions about what to build, integrate, or buy, and how to extend existing Intuit platforms. • Build reusable capabilities. Lead engineering for permission-aware context, agent orchestration, business-system integrations, and evaluation. Enable teams to deliver new workflows using common components. • Own difficult engineering problems through production. Write code, develop reference implementations, lead design reviews, and resolve issues involving distributed execution, data freshness, identity, and recovery from partial failures. • Design dependable human–AI collaboration. Define when agents can act, when approval is required, and how work returns to a person. Make agent actions understandable, traceable, and recoverable. • Set the production quality bar. Establish evaluation datasets, release criteria, monitoring, and incident practices. Balance task accuracy, latency, reliability, privacy, and cost throughout the system lifecycle. • Deliver measurable improvements in work. Partner with product managers and functional leaders to understand current workflows, select valuable opportunities, and measure improvements in completion time, quality, and employee effort. • Multiply engineering capability. Mentor Staff and Senior Staff engineers, develop shared technical standards for quality, security, and maintainability, and align teams on consequential architecture decisions. Communicate technical tradeoffs clearly to senior leaders. Qualifications • 15+ years of software engineering experience, including substantial ownership of large enterprise systems and complex distributed architectures. • Demonstrated technical leadership across multiple teams, with a record of turning long-term architectural direction into shipped software. • Hands-on experience deploying AI capabilities into production, including language-model APIs, retrieval, context engineering, tool execution, and agent orchestration. • Strong programming and system-design skills, with depth in Python, Java, TypeScript, or comparable languages. • Experience building cloud services and integrating enterprise applications, identity systems, and data platforms. • Practical experience evaluating AI behavior, diagnosing failures, and improving quality, security, performance, and operating cost. • Sound judgment about where AI adds value and where deterministic software or human decisions are more appropriate. • The ability to influence without direct authority, develop technical leaders, and make decisions amid uncertainty. • A degree in Computer Science or a related field, or equivalent practical experience. • Experience with employee productivity platforms, enterprise workflow automation, developer tooling, and regulated or sensitive data environments would be valuable • Success means employees complete important workflows faster with less rework; teams can build on reusable capabilities; and deployed systems meet explicit quality, reliability, and cost targets. You own technical architecture and engineering execution, partnering with product and functional leaders on priorities, workflow policy, and adoption. Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: Mountain View $261,500 - $353,500

Requirements

Must-haves

Define the technical direction. Establish a multiyear architecture and roadmap for AI-powered work. Make clear decisions about what to build, integrate, or buy, and how to extend existing Intuit platforms.
Build reusable capabilities. Lead engineering for permission-aware context, agent orchestration, business-system integrations, and evaluation. Enable teams to deliver new workflows using common components.
Design dependable human–AI collaboration. Define when agents can act, when approval is required, and how work returns to a person. Make agent actions understandable, traceable, and recoverable.
Set the production quality bar. Establish evaluation datasets, release criteria, monitoring, and incident practices. Balance task accuracy, latency, reliability, privacy, and cost throughout the system lifecycle.
15+ years of software engineering experience, including substantial ownership of large enterprise systems and complex distributed architectures.
Demonstrated technical leadership across multiple teams, with a record of turning long-term architectural direction into shipped software.
Hands-on experience deploying AI capabilities into production, including language-model APIs, retrieval, context engineering, tool execution, and agent orchestration.
Strong programming and system-design skills, with depth in Python, Java, TypeScript, or comparable languages.
Experience building cloud services and integrating enterprise applications, identity systems, and data platforms.
Practical experience evaluating AI behavior, diagnosing failures, and improving quality, security, performance, and operating cost.
Sound judgment about where AI adds value and where deterministic software or human decisions are more appropriate.
The ability to influence without direct authority, develop technical leaders, and make decisions amid uncertainty.
A degree in Computer Science or a related field, or equivalent practical experience.
Experience with employee productivity platforms, enterprise workflow automation, developer tooling, and regulated or sensitive data environments would be valuable
Mountain View $261,500 - $353,500

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

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