Product Manager, Enterprise Core Platform

Job Description

Scale AI is hiring a Product Manager to own the core infrastructure layer that every forward-deployed engineering team builds on top of. This is a foundational platform role: you'll decide what has to be true at the infrastructure level before anything can ship reliably, and you'll hold the line on quality as the company scales its agentic AI deployments across the world's largest enterprises and government agencies.

You won't be tracking a feature list handed down from someone else. You'll be the person who defines what "production-ready" means for the platform itself — deciding what gets built into core versus what stays a one-off solution, and sequencing that work against real customer commitments and engineering capacity.

Key Responsibilities

• Set the technical and product foundation that all downstream deployment teams rely on, across every core capability area
• Prioritize and sequence platform investments based on live customer commitments and delivery-team velocity, not just technical interest
• Track patterns emerging from field deployments and make the call on which ones are mature enough to become permanent platform capabilities
• Hold every shipped capability to a bar where customers can rely on it without extra scrutiny
• Reduce repeated infrastructure work for delivery teams by building secure, observable, and broadly deployable platform primitives — including tooling for agent evaluation and reasoning over data
• Partner closely with platform engineering, forward-deployed product managers, and business unit leaders to keep the roadmap grounded in what's actually blocking progress

Requirements

• 6+ years in product management, with substantial time specifically owning platform, infrastructure, or developer-facing products at a production standard
• A track record of defining and shipping platform capabilities — not just building features on infrastructure someone else designed
• Strong judgment for sequencing competing priorities under incomplete information, without creating team churn
• Enough technical depth to hold a real conversation with engineers about tradeoffs in infrastructure, authentication, observability, deployment, and agent runtime systems
• A demonstrated habit of following through and owning outcomes across teams, even without formal authority over them
• Communication style that adapts cleanly across audiences — engineers, product peers, and executives

Preferred

• Hands-on experience with AI/ML platform infrastructure — agent frameworks, evaluation pipelines, fine-tuning systems, or production observability for AI
• Background deploying software into constrained environments such as government, regulated industries, or air-gapped networks
• Prior experience as a platform or infrastructure PM where field teams' work fed directly back into core product decisions