Scale AI’s Public Sector business is growing quickly as government agencies adopt AI to support critical national security, defense, and public sector missions. We are seeking a hands-on Engineering Manager to lead our Frontier AI Infrastructure team within Public Sector Engineering. This is a 50/50 role: 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 the latest AI tools, managing networking, debugging latency, and tracking pricing/usage metrics for AI models. You'll lead technical discussions on the frontlines with cloud vendors and customers to deliver on critical contracts and debug platform issues, and you'll partner upstream with Product to catch issues before they break, moving the team from "infra-only debugging" to proactive integration testing.

You will:

As a manager - 50/50 management and hands on coding experience.

• Lead, coach, and grow a team of engineers — own hiring, onboarding, performance, and career development.
• Set technical direction and quarterly priorities for the inference layer, and hold the team accountable to delivery on customer and contract commitments.
• Run the operational rhythm of the team: sprint planning, on-call rotation, incident review, and postmortems.
• Partner with Product, Program, and Deployed Engineering leadership to translate customer and mission requirements into roadmap.
• Represent the team in customer engagements and vendor escalations, including with government stakeholders.
• Design and implement secure, scalable backend systems for Public Sector customers, leveraging Scale's modern cloud-native AI infrastructure.
• Own services and systems alongside your team, define their long-term health goals, and improve the health of surrounding components.
• Stay in the code: review PRs, debug production issues, and take on meaningful technical work yourself.

Must have:

• At least 1-2+ years of direct people management experience leading a team of software engineers (hiring, performance management, and career development), plus a strong track record as a hands-on individual contributor.
• At least an active Secret clearance, and the ability and willingness to up-level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a Secret clearance.
• Willingness to remain hands-on in the code — this is not a purely people-leadership role.

Ideally you'd have:

• Full Stack Development: Proficiency in both front-end and back-end development, including modern web frameworks, programming languages, and databases. Experience developing and delivering software to air-gapped and isolated environments is a plus.
• Cloud-Native Technologies: Understanding of containerization (e.g., Docker) and orchestration (e.g., Kubernetes). Familiarity with cloud platforms (AWS, Azure, GCP) and experience developing and deploying applications in cloud-native environments.
• Security Focused: Experience with federal compliance frameworks and requirements (e.g., Cloud SRG, FedRAMP, STIG Benchmarks). Experience delivering software and technical solutions that meet strict security and regulatory requirements.
• Team Building: Experience building or scaling a team from a small size, and setting engineering standards (code review, testing, on-call) that stick.
• Problem Solving: Strong analytical skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to technical obstacles.
• Collaboration and Communication: Excellent interpersonal and communication skills to collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences.
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to evolving requirements in a fast-moving AI landscape.
• Must be able to support work 3–4 days a week from the DC office.