Forward Deployed Product Manager, Public Sector
Application analysis
Forward Deployed Product Manager, Public Sector at Scale AI is a forward deployed ai company role for engineers who want customer-facing technical work with real deployment ownership.
Reading this role
This Forward Deployed Engineer role centers on embedded customer delivery — discovery, prototyping, integration, and production rollout. Key signals from the listing: Government / DoD context, Senior scope.
About Scale AI
This company is building AI products where forward deployed engineers translate capabilities into customer outcomes quickly. The role is anchored in New York, DC, so expect on-site customer work in that region.
Signals in the listing
Stand out for Forward Deployed Product Manager, Public Sector
- Lead your application with one paragraph tying Forward Deployed Product Manager, Public Sector to a specific customer or deployment you owned — Scale AI hires for shipped outcomes, not tool lists.
- Prepare a 5-minute “week one on site” plan: who you would meet, what you would inspect in their stack, and what artifact you would deliver by day five.
- Show you can go from discovery notes → working integration → production checklist without needing a large internal team.
- State clearance status clearly up front (active, expired, or eligible) and mention any prior NIPR/SIPR, IL5, or government cloud accreditation work — recruiters filter on this early.
- This role is tied to New York, DC — mention willingness to work on-site with customers and any existing ties to that market (clients, partners, or domain knowledge).
Stand out at Scale AI
- Demonstrate rapid prototyping with a concrete example — Scale AI will probe for specifics, not buzzwords.
- Demonstrate customer discovery with a concrete example — Scale AI will probe for specifics, not buzzwords.
- Expect questions about real deployments, safety tradeoffs, and how you partner with customers on week one.
- Read recent engineering blog posts, product launches, and customer stories on scale.com — reference one explicitly in your outreach to show genuine interest.
Tailored from this listing’s title, company, and description. Always verify requirements on the company careers page before applying.
Role description
Scale is accelerating the development of AI across the world's most important organizations, including the U.S. Department of War (DoW), its constituent services, and the broader U.S. National Security industry. The Product Manager, Public Sector will lead Scale's product efforts across two connected focus areas — military planning and real-time AI and Alerting (LUX) — shaping real production outcomes and translating messy operational reality into high-signal input for the core platform. This is not a roadmap PM, a CSM, or a solutions engineer. This PM owns product outcomes for a cross-cutting portfolio of AI and data capabilities: earning deep trust with senior military, civilian, and mission stakeholders, driving deployments to production inside classified and operationally constrained environments, identifying where the product is the bottleneck vs. execution, and feeding durable, specific signal back to Scale's platform team. The best candidates have shipped AI or real-time data products into defense or other large, security-constrained organizations and can tell the difference between a customer's stated request, their actual problem, and what the platform should do.
What You'll Do
Own product outcomes across Scale's military planning portfolio and/or its highest-impact national security accounts for LUX, spanning multiple DoW and National Security stakeholders and use cases. You are the accountable PM for product delivery and customer value. Translate operational reality into high-signal product input for engineering and platform teams — specific, evidence-backed product perspective with tradeoffs articulated, not requirements docs. This includes military planning workflows (e.g., the Joint Planning Process) and modeling/simulation requirements (e.g., AFSIM), as well as real customer workflows, latency/throug