Principal Product Manager, AI Platform

Gigawatt

3h • Remote

About The Position

We are seeking a Principal Product Manager to own the AI platform roadmap and drive strategy for agent infrastructure built on our data fabric. This role involves making build-versus-buy decisions in a rapidly evolving AI tooling landscape. You will define both build paths, including the SDK and code-first experience utilities currently use, and drive the no-code builder that empowers SMEs to ship agents themselves. A key aspect of this role is deciding what gets abstracted, what remains code-based, and how these two approaches converge over time. You will work closely with design partners to define high-value MVPs, build them with real utility customers, and iterate rapidly on friction and edge cases. The role also encompasses owning the developer and builder experience, including API and SDK design, documentation, sandboxes, templates, onboarding, and the entire path from first agent to production deployment. Furthermore, you will define how agent quality is measured, both before and after release, including golden sets, regression suites, online evaluations, and trace/audit records. You will ensure customers have visibility into their own agents and make critical build-versus-buy decisions for tools like LangSmith and Arize, owning the decision on where trace data resides. Designing for human-in-the-loop interaction, including autonomous actions, approval pauses, and state management, is also a core responsibility. You will own trust, tenancy, and governance, covering explainability, auditability, per-tenant data isolation, customer-controlled retention, least-privilege access, and safe autonomy, particularly for agents built by non-developers. Owning the commitments associated with shipping externally, such as versioning, backwards compatibility, deprecation policy, SLAs, support models, and product input into packaging and pricing, is crucial. You will execute by driving with engineering and design to release production-ready capabilities on compressed timelines, defining use cases and technical requirements, collaborating on data models and API design, and conducting product testing. Ultimately, you will own outcomes by setting KPIs and managing dependencies across the platform. This role requires wearing many hats and taking on new ownership areas as priorities evolve.

Requirements

• 8+ years in product management.
• 2+ years on AI or ML systems.
• Significant time on a platform or product that customers outside your own company built on top of.
• Shipped external platform products: APIs, SDKs, or an application builder that customers depended on in production.
• Experience with versioning and deprecation, support escalations, security questionnaires.
• Understanding the difference between an internal tool and a product someone signs a contract for.
• Working fluency in modern AI systems: LLMs, retrieval, tool use, guardrails, and their cost, latency, and reliability tradeoffs.
• Ability to read a trace and diagnose failure points (retrieval, prompt, tool schema, model).
• Experience designing eval sets and shipping against a quality bar.
• Ability to hold your own in an architecture review and write technical specs engineers respect.
• Experience shipping software into regulated, multi-tenant environments (financial services, healthcare, energy, or public sector).
• Experience with tenant isolation, explainability, data lineage, retention, and least-privilege access.
• Treat security and compliance review as a design input.

Nice To Haves

• Experience with low-code, configuration-driven, or builder-style products.
• Hands-on familiarity with a modern agent framework, ideally LangGraph or LangChain: graph-based orchestration, state and checkpointing, tool and schema design, and multi-agent handoffs.
• Experience building on a managed model platform, ideally AWS Bedrock, including model selection tradeoffs, guardrails, throughput and cost management, and VPC, IAM, and data residency constraints.
• Comfort reasoning about data models, integration across messy enterprise source systems, and streaming versus batch.
• Utility or energy sector exposure.
• Background in software engineering, ML, or data engineering before moving into product.
• Experience with Jira, Figma, and standard product management tools.

Responsibilities

• Own the AI platform roadmap, driving strategy and roadmap for agent infrastructure.
• Make build-versus-buy calls across AI tooling.
• Define the SDK and code-first experience utilities use.
• Drive the no-code builder for SMEs to ship agents.
• Decide what gets abstracted, what stays code, and how they converge.
• Define high-value MVPs and build them with utility customers.
• Iterate fast on friction and edge cases.
• Own developer and builder experience: API and SDK design, documentation, sandboxes, templates, onboarding, and the path to production.
• Own evaluation and observability: Define agent quality measurement (golden sets, regression suites, online evals, trace/audit records).
• Give customers visibility into their own agents.
• Make build-versus-buy calls for tools like LangSmith, Arize, and own trace data location.
• Design for human-in-the-loop: Define autonomous actions, approval pauses, state, interrupts, and replay.
• Own trust, tenancy, and governance: Explainability, auditability, data isolation, retention, access, and safe autonomy.
• Own external shipping commitments: Versioning, backwards compatibility, deprecation policy, SLAs, support model, packaging, and pricing.
• Execute: Drive with engineering and design to release production-ready capabilities on compressed timelines.
• Define use cases and technical requirements.
• Collaborate on data model and API design.
• Conduct product testing.
• Own outcomes: Set KPIs and manage dependencies.
• Wear many hats and take on new ownership areas.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed