Principal Product Manager, AI Platform

About the role

We are seeking a Principal Product Manager for Gigawatt’s AI Platform team. The platform is not an internal enabler; it is the product we put in our customers' hands. Your focus is the agent layer, which turns unified context into secure, explainable, and auditable agents.

Responsibilities

• Drive strategy and roadmap for the agent infrastructure built on our data fabric, making build-versus-buy calls in a fast-moving AI tooling landscape.
• Define the SDK and code-first experience utilities use today, and drive the no-code builder that lets their SMEs ship agents themselves.
• Decide what gets abstracted, what stays code, and how the two converge over time.
• Ship with design partners, define high-value MVPs, build them with real utility customers, and iterate fast on friction and edge cases.
• Own API and SDK design, documentation, sandboxes, templates, onboarding, and the paved path from first agent to production deployment.
• Own evaluation and observability, define how agent quality is measured before and after release, and give customers visibility into their own agents.
• Design for human-in-the-loop, define where agents act autonomously, pause for approval, and how state, interrupts, and replay work in practice.
• Own trust, tenancy, and governance, explainability, auditability, per-tenant data isolation, customer-controlled retention, least-privilege access, and safe autonomy.
• Own the commitments that come with shipping externally, including versioning, backwards compatibility, deprecation policy, SLAs, the support model, and the product input into packaging and pricing.
• Execute by driving with engineering and design to release production-ready capabilities on compressed timelines, and manage dependencies across the platform.
• Own outcomes by setting KPIs and managing dependencies across the platform.

Qualifications

• 8+ years in product management, including 2+ years on AI or ML systems, and significant time on a platform or product that customers outside your own company built on top of.
• Platform experience: You have shipped APIs, SDKs, or an application builder that customers depended on in production. You have lived versioning and deprecation, support escalations, security questionnaires, and the difference between an internal tool and a product someone signs a contract for.
• AI systems depth and eval judgment: Working fluency in modern AI systems: LLMs, retrieval, tool use, guardrails, and the cost, latency, and reliability tradeoffs that come with them. You can read a trace and tell whether a failure was retrieval, prompt, tool schema, or model, you have designed eval sets, and you have shipped against a quality bar rather than a demo.
• Regulated, multi-tenant environments: You have shipped software into an environment where someone outside your company audits what it did: financial services, healthcare, energy, or public sector. You have a real point of view on tenant isolation, explainability, data lineage, retention, and least-privilege access, and you treat security and compliance review as a design input rather than a launch blocker.

What We Offer

• Competitive salary and equity.
• The chance to shape a transformative AI product in a vital industry with a rock-star team.
• Comprehensive benefits: health insurance, remote flexibility, and 401k match.