We're looking for a Product Manager to join Procore's Product & Technology Team within Datagrid, Procore's Agentic AI product. In this role, you'll lead the charge in the "Agentic Era" for a trillion-dollar industry, architecting the intelligent engine that transforms fragmented construction data into autonomous, mission-critical decisions. Your primary goal is to build a robust, multi-modal data foundation spanning indexing, ingestion, and retrieval across every format project teams work in-from text documents and schedules to blueprints, photos, and BIM models.
As a Product Manager, you'll partner with world-class Engineering, Architecture, and Data teams to ship world-class AI that moves the needle on how the physical world is built. You'll focus your energy on backend technical execution, systems thinking, and product excellence to turn unstructured, chaotic construction data into precise, high-performance retrieval strategies. Use your platform mindset and technical discovery skills to define the foundational data backbone for AI-driven construction. This position will report to our Senior Director, Applied AI and be located in our San Francisco office. If you're ready to tackle highly scalable, complex systems that power autonomous agent actions, join us!
What you'll do:- Define and execute the technical product strategy for our multi-modal indexing and retrieval architecture, ensuring it serves as a highly precise foundation for all search and AI workflows.
- Own the roadmap for data indexing coverage and freshness, optimizing target latency so newly created project documents, drawings, and blueprints are instantly retrievable.
- Partner with engineering and architecture leads to drive ingestion pipeline reliability, establishing strict standards for uptime, error rates, and schema fidelity across diverse data connectors.
- Architect a graduated search depth strategy that seamlessly routes queries between shallow search for rapid speed and deep search for multi-layered context.
- Optimize retrieval quality and context precision specifically to support autonomous agent actions, moving far beyond passive Q&A into execution-ready data delivery.
- Tackle data scale and information noise by utilizing deep search techniques to cluster, summarize, and extract core themes at the retrieval level.
- Establish performance metrics and evaluation frameworks, leveraging tools like LLM-as-a-judge to continuously measure and improve search recall and response quality.
- Collaborate across the Datagrid division to align backend retrieval capabilities with downstream AI workflows, ensuring our core data engine scales effectively.
What we're looking for:- BS or MS degree in Computer Science, Engineering, or a related discipline, or equivalent practical work experience.
- 3+ years of product management experience, with a proven track record of handling enterprise-class software, databases, or complex data platforms.
- Deep technical understanding of LLMs, Retrieval-Augmented Generation (RAG), search indexing architectures, or vector databases.
- Exceptional platform and systems thinking skills, with an innate ability to understand how data moves through complex, distributed environments.
- Proven ability to navigate ambiguity in highly technical problem spaces, distilling multifaceted, abstract ideas into clear requirements that drive engineering consensus.
- Strong customer-centric discovery mindset, showing proficiency in translating complex end-user workflows into technical backend systems requirements.
- Outstanding cross-functional collaboration skills, with a demonstrated ability to lead through influence and build trust across engineering and architecture teams.
Experience in B2B SaaS or Construction Tech handling multi-modal datasets (drawings, photos, BIM models, or schedules) is a significant plus.
Additional InformationBase Pay Range:129,996.00 - 178,744.50 USD Annual
This role may also be eligible for Equity Compensation and/or Bonus Incentive Compensation. Procore is committed to offering competitive, fair, and commensurate compensation. Actual compensation will be based on a candidate's job-related skills, experience, education or training, and location.
