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About The Role
Volta builds and operates large-scale GPU compute infrastructure for AI workloads. Our platform is Kubernetes-native, spans multiple regions, and delivers virtual machines, storage, and networking through a fully automated infrastructure stack built on custom Kubernetes operators.
Platform Engineers work at the intersection of infrastructure and software development. You will translate three key inputs into durable platform capabilities: product roadmap requirements from the product team, operational learnings from the bring-up team, and security guidance from the security engineering team.
What You Will Be Doing
- Design and implement Kubernetes operators and controllers that manage the lifecycle of compute, storage, and networking resources
- Work closely with the product team to understand roadmap requirements and implement the platform capabilities that support them
- Collaborate with the bring-up team to identify operational pain points and turn them into scalable platform features
- Improve and extend the northbound API layer — the interface between user-facing services and the underlying infrastructure platform
- Build and extend confidential computing capabilities across the platform stack — from secure bare metal and confidential VMs to Confidential Containers (CoCo)
- Integrate security guidance from the security engineering team into platform-level controls and remediate security findings at the platform layer
- Build platform capabilities around networking: reliability, performance, and observability of the overlay and underlay network stack
- Contribute to storage platform improvements: provisioning workflows, attachment reliability, performance tuning, and failure handling
- Own observability as a platform concern — instrument services, define meaningful metrics, and build tooling that gives the team visibility into platform health
- Participate in code review, technical design discussions, and cross-team collaboration in an Agile (Kanban or Scrum) environment
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What You Bring
- 3–5 years of software engineering experience, with a meaningful portion spent on infrastructure or platform systems
- Working proficiency in at least one relevant language — Python, Go, or Rust — with experience writing production-grade backend services or automation, and a willingness to work across languages as the codebase evolves
- Solid understanding of Kubernetes internals: the control loop model, CRDs, controllers/operators, and reliable reconciliation logic
- Comfortable working close to the infrastructure layer — Linux, networking fundamentals, and distributed systems behaviour
- Experience designing and building APIs or service interfaces that other teams depend on
- Strong engineering fundamentals: clean code, testing, version control, code review, and CI/CD practices
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Nice to Have
- Fluency with AI-assisted development, and interest in scaling agent-assisted workflows across the team (agentic CLI tools, MCP, skills, APIs) to amplify delivery.
- Familiarity with confidential computing technologies: TEEs, AMD SEV, Intel TDX, or Confidential Containers (CoCo)
- Experience integrating security requirements into platform or infrastructure systems
- Familiarity with high-performance networking: overlay protocols, BGP, RDMA, or packet-processing frameworks
- Hands-on experience with distributed storage systems (Ceph or similar) at an engineering level
- Background building Kubernetes operators using frameworks such as Kopf, controller-runtime, or similar
- Experience with observability tooling: Prometheus, Grafana, OpenTelemetry, or structured logging in distributed systems
- Exposure to GPU infrastructure or HPC environments
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