Principal Engineering Product Manager, AI Workflow Enablement

Intuit’s AI Transformation Org is changing how 18,000+ employees do their most important work. We bring AI agents into the everyday workflows of Finance, Legal, Marketing, Customer Success, and People & Places. The people doing the work spend less time on coordination and more time on the decisions that need their expertise. We need a Principal who can scale this across the company without taking it over. This role is the engine that gets AI-redesigned workflows into production and keeps them there. You partner with AI Champions inside each non-engineering function. You apply approved enterprise blueprints to high-friction, repeatable workflows. You set measurable baselines before redesign. You make adoption stick after the central team steps back. Your success is measured by what the function can do after you leave, not by what you personally redesigned. You partner closely with the People & Places AI Workforce Transformation team, the Enterprise Solution Architect, the Telemetry and Insights Lead, and senior operating leaders across Intuit’s most consequential non-engineering functions. Responsibilities

• Drive blueprint-led redesign with AI Champions across non-engineering functions. Apply approved blueprint patterns to the workflows we prioritize. Coach Champions through configuration, integration, evaluation, and rollout in their real work, not in training settings.
• Build and validate before you scale. Personally prototype agentic workflow configurations, working closely with engineering partners and directly with LLM APIs or agent tooling to test feasibility. Validate the design meets quality and reliability standards before a function adopts it.
• Hold the line on blueprint standards. Every redesign uses approved workflow logic, agent configuration standards, integration patterns, governance guardrails, and measurement contracts. Push back on bespoke designs that fragment the enterprise architecture.
• Design redesigns to stick. Set baselines before launch. Instrument the pre-state with the Telemetry and Insights Lead. Align role expectations and habits with HR Craft Leaders. Validate the post-state. Treat behavioral adoption as a design constraint from day one, not a retrofit.
• Drive blueprint adoption, not workflow possession. The redesigned workflow is the default execution model in production. The function owns it after you step back. The hand-off is the deliverable, not the redesign itself.
• Surface friction back to platform and architecture. Identify where blueprint patterns break down, where the platform is missing capability, and where governance creates drag. Feed signal to the Enterprise Solution Architect and the platform engineering team. The platform should compound with every redesign.
• Connect workflow redesign to workforce evolution. Every redesign changes what the people doing the work need to know, do, and decide. Partner with HR Craft Leaders and the People & Places AI Workforce Transformation team. Role expectations, AI proficiency, hiring criteria, and learning pathways evolve with the workflow, not after it.
• Maintain the redesign portfolio view. Make redesigns in flight, baselines committed, value captured, and risk visible at any moment. Keep prioritization honest. Resist pressure to take on work that does not meet the bar.

Qualifications Qualifications

• 12+ years of progressive experience designing, building, or operating production AI/ML systems, agentic workflows, or enterprise workflow platforms.
• Engineering or technical background required: you have written production code, built technical prototypes, or held a hands-on technical role (e.g., software engineer, ML engineer, forward-deployed engineer) at some point in your career.
• Currently and personally building agentic workflow prototypes in your day-to-day work (e.g., working directly with LLM APIs, agent frameworks, MCP tooling).
• At least 3 years driving change inside other people’s organizations. This could be embedded with a business function, a forward-deployed engineering team, or a transformation function.
• Demonstrated track record of taking AI-powered workflows from prototype into in-production adoption at enterprise scale.
• Experience influencing and aligning VP-level and above stakeholders on workflow strategy and investment decisions.
• Bachelor’s degree required. Computer Science, Engineering, or a related technical field preferred.

Preferred

• Master’s degree in Computer Science, Engineering, or a related technical field.
• Background in enterprise HR, Finance, Legal, Marketing, or Customer Success technology. These are the functions where this role will spend most of its time.
• Experience designing or implementing responsible AI frameworks, evaluation pipelines, or AI governance programs.
• Prior experience as a forward-deployed engineer or AI solutions architect inside a customer’s organization.

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will 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 $243,000 - $328,500 San Diego, CA $230,000- $311,000