Director of Product – Public Safety AI & Intelligence Solutions

Motorola Solutions•Illinois, US Offsite, MA

3d•$170,000 - $200,000•Onsite

About The Position

As the Director of Product, you will own the vision, strategy, and execution of our new, high-impact intelligence portfolio. We need an AI-native thinker with deep technical awareness of data architecture, cross-platform interoperability, and modern APIs. Crucially, you will lead the evolution from passive data tools to active automation by defining and deploying autonomous AI agents capable of executing complex knowledge work for public safety professionals. Because your users will span from Command Staff and Chiefs making macro decisions, to active supervisors, down to frontline responders facing high-stress situations, a relentless focus on intuitive, mission-critical User Experience (UX) is paramount.

Requirements

10+ years of product management or solution leadership experience in complex data analytics, enterprise SaaS, or intelligence platforms.
Proven experience managing products that require complex cross-platform data integration, API ecosystems, or federated search.
Technical comfort with modern AI frameworks, LLM/LMM engineering, agentic workflows, or graph databases.
A strong track record of working with UX/UI design teams to simplify complex, heavy data layers into clean, high-adoption user interfaces.
Legal authorization to work in the U.S. indefinitely is required.
Employer work permit sponsorship is not available for this position.

Nice To Haves

Direct experience working within or building software for the Public Safety / Government sector.
Familiarity with the technical architecture of public safety data systems: Computer-Aided Dispatch (CAD), Records Management Systems (RMS), Automated License Plate Readers (ALPR), and Real-Time Crime Centers (RTCC).

Responsibilities

Own the end-to-end lifecycle of the new intelligence suite, positioning it as the premier alternative to market incumbents.
Define the functional frameworks, safety boundaries, and task-flows for autonomous AI agents capable of automating deep knowledge work and multi-system data synthesis.
Define requirements for robust data bridges, APIs, and ingestion pipelines that cleanly unify data across legacy on-premise infrastructure and modern cloud platforms.
Drive product workflows using advanced machine learning capabilities, including automated report summarization, natural language querying, entity resolution, and anomaly detection.
Ensure all analytical models and AI agents strictly adhere to CJIS requirements and rigorous data privacy boundaries, maintaining explicit "human-in-the-loop" verification mechanisms.