Principal Technical Product Manager, Enterprise AI Workflow Enablement

Intuit

Confirmed live today High trust

Quick summary

Work type: On-site
Location: Mountain View, CASan Diego, CA
Salary: $243,000–$328,500 / yr
Posted: 119 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 $204k

This role $286k

$130k $350k

below market most similar roles pay here above market

This role pays more than 95% of similar roles. Most pay $177,250–$230,200 — the blue band above. At the midpoint, this role pays about $286k versus about $204k 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 · Principal Technical Product Manager, Enterprise AI Workflow Enablement

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JOB TITLE: Principal Technical Product Manager, Enterprise AI Workflow Enablement The Principal Technical Product Manager, Enterprise AI Workflow Enablement joins the AI Transformation Org to integrate AI agents into the everyday workflows of non-engineering functions like Finance, Legal, and Marketing. You will partner with the People & Places AI Workforce Transformation team to drive blueprint-led redesigns of high-friction, repeatable workflows. Your daily responsibilities include personally prototyping agentic workflow configurations, working directly with LLM APIs and agent tooling to test feasibility, and coaching AI Champions through configuration and rollout. You must ensure designs meet quality standards, governance guardrails, and measurement contracts while ensuring long-term behavioral adoption. This role requires an engineering background, experience with production AI/ML systems, and the ability to translate complex technical requirements into scalable enterprise solutions across diverse business units.

What does a Technical Product Manager earn in California?

Median $200000 from 31 postings across 11 companies.

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Skills

AI LLM APIs Agentic Workflows AI Governance Evaluation Pipelines Telemetry Production Code MCP Tooling Responsible AI

What you'll do

Drive blueprint-led redesigns of high-friction workflows across non-engineering functions.
Personally prototype and validate agentic workflow configurations using LLM APIs and agent tooling.
Enforce enterprise standards for workflow logic, agent configuration, and governance guardrails.
Establish performance baselines and instrument telemetry to measure post-redesign adoption and success.
Ensure functional teams own and maintain redesigned workflows after the initial transition.
Identify and report platform limitations or blueprint failures to the architecture and engineering teams.
Align workflow changes with workforce evolution, including updated role expectations and learning pathways.
Maintain a portfolio view of all active redesigns to track progress, value, and risk.

What we're looking for

12+ years of progressive experience designing, building, or operating production AI/ML systems, agentic workflows, or enterprise workflow platforms.
Engineering or technical background required, including experience writing production code or building technical prototypes.
Currently and personally building agentic workflow prototypes using LLM APIs, agent frameworks, or MCP tooling.
At least 3 years of experience driving change inside other people’s organizations.
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.
Master’s degree in Computer Science, Engineering, or a related technical field (preferred).
Background in enterprise HR, Finance, Legal, Marketing, or Customer Success technology (preferred).
Experience designing or implementing responsible AI frameworks, evaluation pipelines, or AI governance programs (preferred).
Prior experience as a forward-deployed engineer or AI solutions architect inside a customer’s organization (preferred).

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