Principal Product Manager, Enterprise AI

Procore Technologies•Austin, TX

3d•$198,240 - $272,580•Hybrid

About The Position

AI is a company-wide priority at Procore. Our leaders are actively engaged, and teams across the business are eager to experiment. Procore exists to improve the lives of everyone in construction, and that starts with our own people: we want Procore to be a place where people do the best work of their careers. AI is a big part of how we'll get there, by putting better tools in everyone's hands, taking routine work off their plates, and freeing up time for more creative and strategic work. To lead that change, we're building a new Enterprise AI Center of Excellence within Procore's Enterprise Technology & Business Platforms team. The team will set the direction for how Procore uses AI across the business, run the programs that bring it to life, and help every team get real value from it. It's a rare chance to build something from the ground up at a company that's serious about AI. We're looking for a Principal Product Manager, Enterprise AI to join the Enterprise AI Center of Excellence. You'll own the strategy and portfolio for AI for operators and builders across the business, meaning how business teams at Procore use and build with AI: which tools and platforms we invest in, which use cases we prioritize, and how we decide. Your goal is to turn AI from a fragmented, team-by-team effort into a coordinated portfolio with clear standards, priorities, and measurable value. This is a business-led technology role, not an infrastructure or engineering position. You'll be the decision owner for enterprise AI tooling. You'll partner with the Principal Architect, Enterprise AI, who leads hands-on technical evaluation, and with AI Platform Engineering, which builds and runs Procore's AI platforms.

Requirements

10+ years of product management experience, including leading platform or internal-tools products at enterprise scale
Hands-on fluency with generative AI tools and a working understanding of LLMs, agents, and connectors, enough to challenge technical recommendations
Demonstrated experience evaluating, selecting, or rolling out AI or automation platforms at enterprise scale, including building business cases with clear cost and value
Experience partnering across engineering, data, and business stakeholders to drive adoption of a new technology or platform
Strong prioritization judgment across competing stakeholders, and comfort saying no
Comfortable operating in ambiguity and building structure where none currently exists
Technically credible while staying focused on business outcomes, and commercially minded about value realization, not technology deployment alone
Proven ability to influence across organizational boundaries without direct authority
Experience partnering with security, legal, and compliance teams on governance
Clear communication with executives, business leaders, and engineers

Responsibilities

Be the product leader for the AI employee experience. Own the roadmap, use case prioritization, adoption strategy, and value delivery for how employees use AI.
Own the enterprise AI roadmap and tool portfolio. Decide which AI tools and platforms Procore invests in, how they're sequenced, and when legacy tools are retired.
Run tool and platform evaluations. Set the evaluation criteria, weigh business value, cost, and portfolio fit, and make clear recommendations. Partnering with the Principal Architect who leads the technical side of each evaluation.
Prioritize the use case portfolio. Score and rank AI use cases from across the business, decide what moves forward and where it's delivered, and stop work that isn't delivering value.
Set governance standards. Define how AI tools, connectors, and use cases are evaluated and approved, in partnership with Security, GRC, and Legal. The Staff TPMs, Enterprise AI run the process day to day.
Own the shared AI asset library. Treat shared skills, Claude Projects, and agent patterns as a product: decide what goes in, keep it current, and drive reuse across teams.
Act as product owner for enterprise agents and Claude. Treat Claude and enterprise-wide agents as internal products: own requirements, priorities, and the roadmap, partnering with AI Platform Engineering on delivery.
Define success and show value. Measure AI investments by time to value, productivity improvement, cycle time reduction, employee experience, risk, and financial impact, treating usage as a floor rather than the finish line. Validate realized benefits with business leaders. Work with Analytics and Finance to show what we're getting for what we spend, and shape vendor and license strategy and build-vs-buy recommendations.
Bring the business case to leadership. Prepare recommendations for the Enterprise AI SteerCo, keep the portfolio aligned with company priorities, and help hold the boundaries between the Center of Excellence and adjacent teams.