Senior Staff Software Engineer – Compute Engineering

We are hiring across multiple engineering levels. Final level alignment is determined by experience, technical expertise, demonstrated impact, and interview performance.  Join the Compute Engineering organization, which builds the scheduling, capacity, and performance systems that run our platform across private and public cloud.    What you get to do in this role: • Design and evolve the compute scheduler and resource-management systems, including placement, prioritization, preemption, and fairness across workloads.  • Build capacity models and forecasts across private and public cloud, and turn them into reservation and placement decisions.  • Establish performance and scale testing: benchmarks, load tests, regression detection, and SLOs for scheduling latency and throughput.  • Apply AI and ML to forecasting, anomaly detection, and placement optimization where they outperform simpler approaches.  • Write and maintain declarative, software-defined infrastructure at scale, with build systems, web services, and automation that are specified, documented, and testable.  • Research and adopt open-source and commercial tools and methods that improve compute efficiency and reliability.  • Partner with networking, orchestration, SRE, and FinOps teams on cross-team designs and cost trade-offs.  • Guide complex technical decisions and design reviews. Challenge assumptions with data, surface architectural risks early, and balance shipping speed with long-term durability.  • Own production reliability and incident response for compute systems, and lead post-incident improvements.  • Mentor architects and senior engineers and build the next layer of technical leadership.  Level expectations  • Senior Staff : Leads the design and delivery of a major component of the compute platform. Drives quality within a team and mentors engineers.  • Principal : Sets technical direction across multiple teams or a major compute area. Shapes architecture, mentors senior engineers and architects, and influences decisions across geographies.  Qualifications To be successful in this role you have: • Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. • 12+ years of related experience in software engineering, cloud, or infrastructure automation with a Bachelor's degree; or 8+ years and a Master's degree; or a PhD with 5+ years of experience; or equivalent experience.  • Deep experience designing multi-tenant, cloud-native SaaS at enterprise scale, including distributed systems, large-scale data systems, APIs, and microservices.  • Experience designing or operating large-scale schedulers or resource managers, such as Kubernetes, Slurm, or internal equivalents.  • Strong programming skills in Go, Python, or Java, with experience in related languages.  • Experience with capacity planning, performance engineering, or load testing at scale.  • Hands-on experience applying ML in production, including models, feature pipelines, or ML platforms. Using AI tools alone is not enough.  • Experience with infrastructure as code and configuration management, such as Terraform and Ansible.  • Comfortable with virtualization and cloud infrastructure across private and public clouds, such as Azure, AWS, GCP.  • Working understanding of IP networking, block and file storage, and load balancers.  • Experience integrating AI into work processes, decision-making, or problem solving.  • Works independently across interconnected systems and investigates root causes without waiting for direction.  • Influences without direct a