Platform Engineer

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. We are building out several platform engineering teams that together own the full stack, from managed bare metal and IaaS through to higher-order platform services. Each team owns a different part of that stack: compute, networking, storage, the control plane and API layer, confidential computing, and the customer-facing surface. The area you work in depends on the team you join and your prior expertise, so no single engineer is expected to cover all of it. Platform Engineers work at the intersection of infrastructure and software development. Across every team, you will translate three key inputs into durable platform capabilities: product roadmap requirements from the product team, operational learnings from the bring-up teams, and security guidance from the security engineering team. The output of this role is production platform code, not configuration, not runbooks. What You Will Be Doing Common across every platform engineering team: Design and implement Kubernetes operators and controllers that manage the lifecycle of platform resources. Work closely with the product team to turn roadmap requirements into the platform capabilities that support them. Collaborate with the bring-up teams to identify operational pain points and turn them into scalable platform features. Integrate security guidance from the security engineering team into platform-level controls, and remediate findings at the platform layer. Treat observability as a platform concern: instrument services, define meaningful metrics, and build tooling that gives the team visibility into platform health. Own the services you build in production, including participation in an on-call rotation, incident response, and the follow-up work that closes structural gaps rather than only the immediate issue. Hold to clean interface and versioning practice on anything other teams or customers depend on, including disciplined handling of breaking changes. Participate in code review, technical design discussions, and cross-team collaboration in an Agile (Kanban or Scrum) environment. Depending on your team and background, you will go deep in some of the following: Control plane and APIs: improve and extend the API layer between user-facing services and the underlying platform, with disciplined versioning and backward compatibility. Compute: build and operate the lifecycle of virtualized and bare metal compute resources. Storage: provisioning workflows, attachment reliability, performance tuning, and failure handling. Confidential computing: build and extend confidential computing capabilities across the stack, from secure bare metal and confidential VMs to Confidential Containers (CoCo). Customer-facing services: the platform surfaces customers interact with directly, including the APIs and interfaces through which they consume capacity, working alongside product and UX. What You Bring 3 to 5 years of software engineering experience, with a meaningful portion spent on infrastructure or platform systems. Strong backend or systems programming experience in a production environment. Our working languages are Python, Go, and Rust; we welcome strong engineers from other compiled or object-oriented languages (for example C++, C#, or Java) who are ready to work across our stack as it evolves. Solid understanding of Kubernetes internals: the control loop model, CRDs, controllers and operators, and reliable reconciliation logic. Comfortable working close to the infrastructure layer: Linux, networking fundamentals, and distributed systems behavior. Experience designing, building, and versioning production-grade APIs or service interfaces that other teams depend on, including disciplined handling of breaking changes and backward compatibility. Experience operating what you build: debugging production systems, and taking part in on-call or incident response. Strong engineering fundamentals: clean code, testing, version control, code review, and CI/CD practices. Nice to Have (But Not Essential) None of these are required. Several map to specific teams, so strength in one or more helps us match you to the right one: Fluency with AI-assisted development: agentic CLI tools, IDE assistants, and orchestrating multiple coding agents through MCP, skills, or APIs to amplify delivery. Depth in Go or Rust beyond working proficiency. 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. Experience building SaaS or PaaS layers on top of an IaaS platform. Exposure to serverless or inference serving infrastructure. Exposure to GPU infrastructure or HPC environments. Experience working distributed across time zones with counterparts in other regions.