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About the Role
As a Staff Software Engineer within our Compute Architecture organization, you will help build the software systems that operate the backbone of our large-scale GPU data centers. The METALDEV team builds Go-based distributed services that bring new infrastructure online, manage hardware lifecycle workflows, monitor production health, and automate safe operations across fleets of GPU servers and rack-scale systems. This is a software-first role at the intersection of distributed systems, production reliability, and hardware-aware automation, where your work directly improves the reliability, safety, and scalability of real-world infrastructure.
What You’ll Do
- Design, build, and operate Go-based services that manage the lifecycle of large-scale GPU data center infrastructure.
- Build automation for data center bring-up, hardware discovery, health monitoring, remediation, and production operations.
- Develop reliable APIs, services, and workflows for managing BMCs, firmware state, server health, and rack-level infrastructure.
- Improve observability, alerting, and operational tooling so production issues can be detected, understood, and resolved quickly.
- Translate incidents and hardware failure modes into software improvements that make the platform more resilient.
- Partner with hardware-adjacent, infrastructure, operations, and software teams to design systems that work safely at fleet scale.
- Provide technical leadership through design reviews, code reviews, architectural guidance, and mentorship.
- Make pragmatic architecture decisions that balance reliability, simplicity, scalability, and operational burden.
Who You Are
- B.S., M.S., or PhD in Computer Science or related field, or equivalent experience.
- 8+ years of software engineering experience with a strong focus on infrastructure, cloud engineering, and distributed databases—particularly within large-scale datacenter and cloud environments.
- Expertise in Go and proven experience building REST/gRPC APIs for mission-critical platforms.
- Strong background in architecting and scaling cloud-native Kubernetes infrastructure and distributed services.
- Proven success in mentoring engineers, leading technical projects, and influencing engineering strategy across teams.
- Experience