Engineering Manager, Frontier AI Infrastructure - Public Sector
Leads and codes alongside a team building secure, cloud-native AI model inference infrastructure for public-sector customers. Requires engineering people-management experience, strong hands-on software development skills, and an active Secret clearance with eligibility for TS/SCI.
About the job
Responsibilities
- Lead, coach, and grow a team of software engineers, including hiring, onboarding, performance management, and career development.
- Set technical direction and quarterly priorities for the model inference layer.
- Own sprint planning, on-call rotations, incident reviews, and postmortems.
- Partner with Product, Program, and Deployed Engineering leadership to translate customer and mission requirements into a 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.
- Own services and systems, define long-term health goals, and improve surrounding components.
- Review pull requests, debug production issues, and contribute hands-on technical work.
Requirements
- 1–2+ years of direct people-management experience leading software engineers, including hiring, performance management, and career development.
- Strong track record as a hands-on individual contributor.
- Active Secret clearance and ability and willingness to obtain TS/SCI with CI Poly.
- Ability to work hands-on in the code.
- Ability to support work 3–4 days per week from the Washington, DC office.
Preferred Qualifications
- Full-stack development experience across front-end and back-end systems, modern web frameworks, programming languages, and databases.
- Experience delivering software to air-gapped and isolated environments.
- Experience with containerization and orchestration technologies.
- Familiarity with AWS, Azure, or Google Cloud and cloud-native application development.
- Experience with federal compliance frameworks and requirements, including Cloud SRG, FedRAMP, and STIG Benchmarks.
- Experience building or scaling small engineering teams and establishing engineering standards for code review, testing, and on-call operations.
- Strong analytical, problem-solving, collaboration, and communication skills.
- Adaptability and willingness to learn new technologies in a rapidly evolving AI environment.
Compensation and Benefits
- Base salary range: $213,600–$267,000 USD.
- Compensation may include equity and benefits.
- Benefits include health, dental, and vision coverage, retirement benefits, a learning and development stipend, generous paid time off, and potentially a commuter stipend.
Skills
Python, Docker, Kubernetes, AWS, Microsoft Azure, GCP, Cloud Srg, FedRAMP, Stig Benchmarks, Backend Development, Frontend Development, Databases, Cloud-Native Architecture, Incident Management, Code Review
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