Primary record

Senior AI Product Manager, Cybersecurity

Scale AI Indexed employerNew York, NY; San Francisco, CA · New York, New York, United States · San Francisco, California, United States
Source-hosted applyChecked 4h agoInternship
Apply at Scale AI

Scale AI receives this application through Greenhouse. Babu Careers does not claim delivery.

Workplace

On-site

Employment

Internship

Published

Aug 11, 2026

Closes

No date supplied

The role

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world's most important decisions

We're looking for a Senior AI Product Manager to build and own Scale's Cybersecurity portfolio — the data, environments, and evaluations frontier labs use to train and measure security capability in their models. This is a build role: you will define the strategy and standards for a product line that does not exist yet.

Security is where the hardest problems in agentic AI now sit. An agent that can find a vulnerability, prove it reproduces, and patch it without breaking the system is doing work that takes a skilled human days. Measuring that honestly requires reproducible execution environments at scale and practitioners who have actually done the work. Scale has the first, proven across SWE-Bench Pro, SWE Atlas, and our contributions to the Terminal-Bench lineage. You will build the second.

You Will

• Own the roadmap and strategy for Scale's Cybersecurity portfolio across training data, RL environments, agentic task suites, and evaluation products — and stand the product line up end to end, from task taxonomy and sourcing through pricing and first external release.

• Define the capability map we train and measure against: vulnerability discovery, proof-of-concept reproduction, patch generation and regression safety, secure code review, supply-chain analysis, malware and binary analysis, detection engineering, and incident triage.

• Make the strategic call on where Scale competes across the offense–defense spectrum — which capabilities we build training data for, which we only measure, and which we decline.

• Partner with ML researchers and security practitioners on task specificat

Requirements

Department: Gen AI Product