Forward-Deployed PM: Defense AI & Real-Time Systems

Scale AI; New York (NY); On-site; USD 210,000 - 345,000; Full time

Job summary

Scale AI is seeking a Product Manager for Public Sector to lead cross-cutting AI and data product initiatives across military planning and real-time alerting (LUX). You will own outcomes, translate complex operational realities into actionable product input, and build trusted relationships with senior DoD and civilian stakeholders.

You will drive deployments in classified environments and balance competing constraints.

Qualifications

• 6+ years in product management, technical program management, or a customer-facing product ownership role.
• Direct experience with DoW or national security community.
• Experience shipping AI or data products into large, constrained, classified, or highly regulated organizations.
• Strong ownership: closes loops, drives outcomes across teams, and follows through.

Responsibilities

• Own product outcomes across Scale's military planning portfolio and LUX engagements, accountable for delivery and customer value.
• Translate operational reality into high-signal input for engineering and platform teams with clear tradeoffs.
• Build trusted advisory relationships with senior military leaders and civilian stakeholders; be the escalation point.
• Drive deployments from contract to production inside classified environments; define production readiness.

Skills

Enterprise deployment ownership

Domain fluency

Product judgment in the field

Customer trust-building

Technical translation

Operating in ambiguity

Clear, precise communication

Travel flexibility

Job description

Scale AI is seeking a Product Manager for Public Sector to lead cross-cutting AI and data product initiatives across military planning and real-time alerting (LUX). You will own outcomes, translate complex operational realities into actionable product input, and build trusted relationships with senior DoD and civilian stakeholders.

You will drive deployments in classified environments and balance competing constraints.