Description
You'll join the Platform Engineering team building and operating Cisco's AI Compute Platform , the GPU infrastructure that powers model training, inference, and LLM workloads at scale.
As a Senior Platform Software Engineer on the Platform Engineering team, you will own the architecture, technical direction, and operation of the control-plane and scheduling systems that make GPU infrastructure usable at scale.
Responsibilities:
- Architect and develop platform control-plane services, APIs, and controllers to manage multi-cluster lifecycle, tenant project onboarding, and GPU quota enforcement across shared and dedicated pools.
- Own the technical architecture for GPU capacity scheduling and allocation , including fractional GPU allocation, multi-tenant isolation, and workload-aware scheduling logic that accounts for training vs. inference differences.
- Drive the design and development of automated capacity-intake, demand-classification, and request-routing tooling that routes workloads to the right cluster and compute pool.
- Architect automated remediation tooling that detects node and workload failures, triggers automated remediation, and optimizes system-wide performance for training and inference workloads.
- Design, build, and scale reliable Kubernetes-based platforms as the foundation of the AI Compute Platform.
- Lead design reviews and set technical standards for platform services, Kubernetes Operators, Controllers, CRDs, and automation built with Go and Python.
- Mentor engineers across the team, raising the bar on cloud-native software engineering practices and platform reliability.
- Drive Infrastructure as Code, GitOps, and CI/CD automation for the platform; participate in on-call rotation, incident response, and postmortem reviews.
Minimum Qualifications:
- Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience.
- 8+ years of software engineering experience building, architecting, or extending Kubernetes-based platforms or large-scale distributed systems, including technical leadership experience.
- Strong software development proficiency in Go or Python, with a proven track record architecting platform control-plane services, custom APIs, Kubernetes Controllers, Operators, or CRDs.
- Hands-on experience building, architecting, or operating batch and accelerator schedulers for GPU or AI/ML workloads.
- Deep experience with GPU scheduling, multi-tenant GPU infrastructure, or managing workloads on accelerated compute platforms.
- Proven track record designing for reliability and operational excellence with Infrastructure as Code, GitOps, CI/CD, and cloud-native observability tools.
Benefits:
- Medical, dental, and vision insurance
- 401(k) plan with Cisco matching contribution
- Paid parental leave
- Short and long-term disability coverage
- Basic life insurance
- Paid time away (vacation, holidays, sick time)
- Optional 10 paid days per year to volunteer
- Annual bonuses for non-sales roles
- Performance-based incentive pay for sales roles