Principal Software Engineer - Kubernetes Platform

About the role

Atlassian India is hiring a Principal Software Engineer for its KubePlat team, which owns the Kubernetes ecosystem powering all Atlassian cloud products. The engineer sets the technical direction for the Kubernetes, compute and AI/ML infrastructure platform, leads engineers across several teams on hard problems and takes large cross-team initiatives from design to launch. The office is in Bengaluru, but eligible candidates can work remotely across India under the TEAM Anywhere arrangement.

Key responsibilities

• Define the architecture and multi-year roadmap for a multi-cloud, cell-based Kubernetes fleet scaling to thousands of clusters.
• Design Kubernetes-native control planes (controllers, operators, CRDs and policies) giving engineers self-serve compute, networking and cloud resources.
• Raise platform reliability and security: reduce blast radius, build safe progressive rollouts, define SLOs, isolate workloads and support compliance such as FedRAMP.
• Lead compute efficiency through autoscaling, bin packing, capacity planning and cost optimisation.
• Build the AI/ML infrastructure on Kubernetes: GPU compute, high-bandwidth low-latency networking and parallel filesystems for training and inference.
• Influence engineering and product leaders globally, set architectural standards and mentor senior engineers.

Required profile

• 10+ years building and operating large-scale cloud infrastructure or platform-as-a-service systems.
• Deep, hands-on Kubernetes expertise in production at scale, including internals, networking, multi-tenancy and building operators and CRDs.
• Strong experience with AWS and/or GCP (EKS/GKE) and distributed systems design.
• Track record of leading technical direction across teams, with strong communication and mentoring skills.

Required skills

• Programming in Go, Python, Java or similar.
• Infrastructure as Code, GitOps/CD (e.g. Terraform, Crossplane, ArgoCD) and observability.
• Nice to have: Kubernetes fleet management, cell-based architectures, sandboxing (gVisor, Firecracker), AI/ML infrastructure (GPU clusters, RDMA, Lustre, etc.) and CNCF open-source contributions.