Product Manager - AI-Native Business Systems

<p><strong>Position: </strong>Product Manager - AI-Native Business Systems<strong><br>Location:</strong> South San Francisco<br><strong>Time Type:</strong> Full Time<br><br></p> <h3><strong>The Opportunity:</strong></h3> <p>Ohalo is moving beyond R&amp;D into a phase of massive operational scale. As our breakthrough "Boosted Breeding™" technology rewrites what is biologically possible in the field, our entire enterprise operation from Commercial Ops and Agentic workflows to backoffice G&amp;A must scale with the exact same ambition. We are seeking a Product Manager to bridge our core <strong>Infrastructure &amp; AI Native Business Systems </strong>efforts with company-wide operational execution.<br><br>This is not a siloed RevOps or traditional Business Intelligence role. Your mandate is company-wide. Partnering across our infrastructure and platform teams, you will expand Ohalo’s core operational capabilities with AI including harnessing agent frameworks, MCP tooling, maintaining skills, etc and ensure best practices are accessible across every department. You will turn foundational AI capabilities into pragmatic, high-impact operational systems, ensuring the whole company runs on a trusted, unified digital layer rather than a patchwork of vibe coded applications. This is a role for a hands-on operator who understands systems and can prototype solutions directly to prove value before hardening into new platform capabilities.</p> <h3><strong><br></strong><strong>Responsibilities:</strong></h3> <ul> <li><strong>Scale Company-Wide AI Deployment:</strong> Partner across engineering teams to extend core AI capabilities across the entire business. Drive company-wide adoption of agent infrastructure.&nbsp;</li> <li><strong>Manage MCP &amp; Tooling Access:</strong> Define and govern Model Context Protocol (MCP) integrations and agent skills. Ensure native agents (spanning leadership team to commercial ops and backoffice G&amp;A) have secure, reliable access to internal tools and systems of record.</li> <li><strong>Improve Evals &amp; Quality Standards:</strong> Stand up evaluation frameworks for operations and establish consistent feedback loops. Monitor AI agent performance, latency, accuracy, and cost-to-serve, continuously refining skills and prompts to ensure high-fidelity outputs.</li> <li><strong>Architect Enterprise Reporting &amp; Ground Truth:</strong> Serve as the company’s absolute metric authority. Define, standardize, and govern KPIs across Commercial, Ops, People, and G&amp;A so leadership makes decisions based on a single source of truth calculated at the system level.</li> <li><strong>Automate Operational Fric