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Stakeholder management

About the job

The AI Solutions & Transformation team builds the engineering backbone that turns Intuit's commercial strategy into production AI systems — the agentic pipelines, creative tooling, and automation that let the business move at the speed AI now demands. As Principal, you own the engineering organization behind that work: you lead the broader product development team, and you're accountable for the technical direction, delivery quality, and growth of everyone building inside this team.

This is not a maintain-the-roadmap role. The AI landscape this team builds against changes every quarter — sometimes every month — and the job is to build a team that treats that as normal rather than disruptive: ship something real, learn fast from what the model, the tooling, or the business actually needs, pivot without drama, and build again. You'll be the person who decides what's worth doubling down on, what gets killed, and how a group of engineers and engineering leads keeps shipping enterprise-grade AI solutions while the ground underneath them keeps moving.

You'll report into GBSG Commercial organization, and you'll work in close, daily partnership with the AI Solutions product management team, who own the product bets this engineering organization builds against. That means part of the job is translating between two worlds: you need enough technical depth to set direction, make build-vs-pivot calls, and earn credibility with your engineers — and enough business fluency to turn product management's priorities into a technical roadmap, and explain what the team is building, and why it matters, in terms a commercial, brand-first audience immediately understands.

Responsibilities

Lead the engineering organization

Manage and grow a team of engineering contractors and FTEs to leading the product development squads building the team's AI systems.

Set the technical direction and engineering quality bar across the full AI Solutions & Transformation portfolio.

Own the build-pivot-kill calls: decide where the team doubles down, where it cuts losses, and where it re-architects as new models, tools, and business priorities emerge.

Build the org's structure and capacity plan so it can run multiple concurrent AI initiatives without you being the bottleneck.

Own delivery and impact

Be accountable for the delivery, reliability, and quality of the AI systems your organization ships into production for the commercial business.

Turn ambiguity into an execution plan: take loosely defined, fast-changing product priorities from the AI Solutions product management team and convert them into a staffed, sequenced build plan for your team.

Establish the operating cadence — planning, prioritization, and review — that keeps a fast-iterating AI team shipping rather than thrashing.

Serve as the escalation point for technical, delivery, or resourcing issues that need a group manager's judgment and authority to unblock.

Partner across the business

Partner day-to-day with the AI Solutions product management team as your primary counterpart — translating product priorities into a staffed technical roadmap, and surfacing technical tradeoffs, risk, and pivots back to them in terms they can act on.

Represent engineering to brand and other cross-functional partners on progress, risk, and the pivots the team is making and why.

Build trust with non-technical stakeholders by communicating clearly, not just correctly.

Build the practice

Establish engineering practices suited to rapid AI iteration: fast experimentation, clear criteria for scaling or killing a bet, and reusable infrastructure so each new capability ships faster than the last.

Set the hiring bar and run the interview loop for engineers and engineering leads joining the team during a period of rapid growth and change.

Coach and develop the managers and leads on your team, including Ashton and Jaga, and own their performance and career growth.

Qualifications

What You'll Bring

8+ years of software engineering experience, including meaningful time leading engineering managers or leads (Group Manager / Senior Manager level), not just individual contributors.

Hands-on technical depth in modern AI and agentic systems — LLMs, RAG, agent orchestration and tool use, prompt engineering

A track record of shipping production AI systems, not demos or proofs of concept, under real delivery pressure.

Demonstrated comfort with fast, repeated iteration: building something, learning it's wrong, pivoting without losing the team's momentum, and building again.

Experience managing engineering within or adjacent to a commercial, brand, or marketing organization, with the ability to translate business and brand goals into technical execution.

Strong stakeholder management and the judgment to partner with senior, non-technical executive leadership.

Experience scaling a technical practice: hiring, leveling, interview loops, and engineering standards.

Bachelor's degree in Computer Science or a related field, or equivalent practical experience.

Preferred

Experience building enterprise-grade AI solutions: RAG pipelines, multi-agent systems, content generation, compliance/QA automation, or similar agentic tooling.

Background in fintech, SaaS, or brand/creative technology.

Experience leading a team through a significant strategic or organizational pivot.

Experience managing managers specifically, rather than only a team of individual contributors.

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: San Diego $247,500 - $335,000