Principal Software Engineer, Compute Scheduling

Quick Facts

• Role: Principal Software Engineer, Compute Scheduling

• Focus: Compute scheduling, capacity forecasting, performance testing, and AI/ML-driven optimization across private and public clouds

Description

Design and evolve compute scheduler and resource-management systems that drive platform performance across cloud environments. Build capacity models and forecasts, establish performance and scale testing with SLOs, and apply AI/ML to improve forecasting, anomaly detection, and placement optimization. Own production reliability for compute systems, lead post-incident improvements, and mentor senior engineers and architects.

Responsibilities

• Design and evolve compute scheduling and resource management (placement, prioritization, preemption, fairness)
• Develop capacity models and forecasts and convert them into reservation and placement decisions
• Set up benchmarks, load tests, regression detection, and SLOs for scheduling latency and throughput
• Apply AI/ML to forecasting, anomaly detection, and placement optimization where it outperforms simpler approaches
• Write and maintain declarative, software-defined infrastructure at scale with build systems, web services, and automation
• Research and adopt open-source and commercial tools to improve compute efficiency and reliability
• Collaborate with networking, orchestration, SRE, and FinOps on cross-team designs and cost trade-offs
• Lead complex technical decisions and design reviews; balance shipping speed with long-term durability
• Own production reliability and incident response; drive post-incident improvements
• Mentor architects and senior engineers; develop next-layer technical leadership

Requirements

• 15+ years of related software engineering experience with a Bachelor’s degree (or 12+ with a Master’s; or PhD with 8+; or equivalent)
• Deep experience designing multi-tenant, cloud-native SaaS at enterprise scale (distributed systems, large-scale data systems, APIs, microservices)
• Experience designing or operating large-scale schedulers/resource managers (Kubernetes, Slurm, or equivalents)
• Strong programming skills in Go, Python, or Java (with related languages)
• Experience with capacity planning, performance engineering, and load testing at scale
• Hands-on ML in production (models, feature pipelines, or ML platforms); not limited to using AI tools
• Infrastructure as code and configuration management (Terraform, Ansible)
• Comfort with virtualization and private/public cloud infrastructure (Azure, AWS, GCP)
• Working knowledge of IP networking, block and file storage, and load balancers
• Ability to integrate AI into decision-making and problem solving
• Works independently across interconnected systems; can investigate root causes
• Influences across multiple teams and geographies without direct authority
• Clear communication and ability to articulate a technical vision
• Learning mindset; integrity and values alignment

Benefits

• Base pay guideline: $221,200–$387,100, plus equity (when applicable) and variable/incentive compensation
• Health plans including flexible spending accounts
• 401(k) with company match; ESPP; matching donations
• Flexible time away plan and family leave programs