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Join Datadog's Compute – Disruption and Workload Placement team as a Staff Engineer to shape the future of capacity orchestration and infrastructure scaling. You'll lead the technical direction of capacity management and workload placement for Datadog's Kubernetes platform, which spans 100,000+ virtual machines across AWS, Google Cloud, and Azure.
In this highly technical, high-impact role, you'll design and build systems that optimize how engineering workloads are scheduled and deployed across regions while balancing capacity constraints, reliability, and performance. You'll develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency. Your work will directly support Datadog's continued growth as AI and cloud-native workloads rapidly expand.
You'll partner across infrastructure teams to evolve multi-region and multi-cloud capacity orchestration, using data and capacity signals to influence infrastructure decisions, forecast growth, and improve workload placement strategies. This is a technical leadership role where you'll influence platform architecture and solve infrastructure challenges without relying on direct management authority.
You bring significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems, with strong programming skills ideally in Go or comparable systems languages. You have hands-on experience with at least one major cloud provider and a strong systems mindset for solving complex infrastructure, scheduling, or capacity management challenges. You're comfortable working with operational data, capacity forecasting, and analytical approaches that inform engineering decisions, with a proven track record of providing technical leadership and influencing architecture across teams.
