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Scale AI is seeking a hands-on Engineering Manager to lead the Frontier AI Infrastructure team within Public Sector Engineering. This is a 50/50 role combining technical leadership with individual contribution—you'll spend roughly half your time writing and reviewing code, and half your time leading, coaching, and growing a small team of engineers.
Your team owns the model inference layer, enabling state-of-the-art models, debugging AI tools, managing networking, optimizing latency, and tracking pricing/usage metrics. You'll lead technical discussions with cloud vendors and government customers to deliver on critical contracts and debug platform issues. You'll partner upstream with Product to shift the team from reactive "infra-only debugging" to proactive integration testing.
Key responsibilities include:
- Lead, hire, onboard, and develop a team of software engineers; own performance management and career growth
- Set technical direction and quarterly priorities for the inference layer; hold the team accountable to customer and contract commitments
- Run operational cadence: sprint planning, on-call rotation, incident review, and postmortems
- Partner with Product, Program, and Deployed Engineering to translate customer and mission requirements into roadmap
- Represent the team in customer engagements and vendor escalations with government stakeholders
- Design and implement secure, scalable backend systems for Public Sector customers using Scale's cloud-native AI infrastructure
- Own services and systems; define long-term health goals and improve surrounding components
- Stay hands-on: review PRs, debug production issues, and take on meaningful technical work
Required qualifications:
- 1–2+ years of direct people management experience leading software engineers (hiring, performance management, career development) plus strong hands-on IC track record
- Active Secret clearance (minimum); ability and willingness to upgrade to TS/SCI with CI Poly
- Commitment to remaining hands-on in code—this is not a purely people-leadership role
- Ability to work 3–4 days per week from the DC office
Ideal candidates will have full-stack development experience (front-end and back-end, modern frameworks, databases), cloud-native technologies (Docker, Kubernetes, AWS/Azure/GCP), federal compliance and security expertise (FedRAMP, STIG, Cloud SRG), team-building and scaling experience, strong problem-solving and analytical skills, excellent cross-functional collaboration, and adaptability in a fast-moving AI landscape.
