Systems Engineering Manager
New York$275k - $330kFull-timePosted 8mo ago
About the role
Engineering Manager to lead a team building Modal's serverless GPU infrastructure. Hands-on leadership with technical contribution, focusing on distributed systems, large-scale data handling, and performance optimization.
Responsibilities
- Recruit, hire, and grow a high-performing team of cloud platform engineers; run regular 1:1s focused on coaching, feedback, and career growth.
- Set clear performance expectations, hold a high bar, and build an environment where engineers do their best work.
- Foster a culture of ownership, accountability, and continuous improvement.
- Drive day-to-day technical decisions through design reviews, code reviews, and architectural discussions.
- Translate the infrastructure roadmap into clear team priorities and milestones, and hold execution against them.
- Establish standards for reliability, performance, and operational excellence; ensure the team owns projects end-to-end, from spec through production.
- Push for good judgment on tooling and architecture, with a bias against unnecessary complexity.
- Partner with product and engineering to align infrastructure work with business priorities; represent your team's progress, capacity, and tradeoffs clearly to leadership.
- Serve as the escalation point for major incidents; drive resolution with urgency and ensure the team learns systematically, feeding those learnings back into infrastructure improvements.
Qualifications
- 10+ years of industry experience, including 3+ years in a leadership role
- Track record building high-performance distributed systems at scale
- Strong background in cloud infrastructure
- Deep knowledge of low-level OS foundations (Linux kernel, file systems, containers, etc.)
- Proficiency in a systems-level language (Rust, C, C++, or Java)
Skills
Required:Distributed systemsCloud infrastructureLinux kernel / OS foundationsSystems programming
Last updated Oct 21, 2026. Interested? Apply on the company site.
About Modal
High-performance AI infrastructure
Bring your own code, and run CPU, GPU, and data-intensive compute at scale. The serverless platform for AI and data teams.
AI infrastructureBatchGPU scalingInferenceML workloadNotebooksObservabilityPlatform
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