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Volta is building a vertically integrated AI infrastructure platform with a mission to make compute as dependable and available as electricity. The company has secured $10B in strategic partnerships, Series A funding from Andreessen Horowitz, and a $5B AI Infrastructure Fund, with 100+ employees across London, Palo Alto, and New York.
You will lead one of Volta's platform engineering capability teams, each owning a defined part of the infrastructure stack: compute, storage, control plane and API layer, confidential computing, networking, or customer-facing surface. This is a hands-on leadership role where you set technical direction, carry accountability for delivery, and manage the people on your team while staying close enough to the code to tackle hard problems yourself.
Key responsibilities include: leading your platform engineering team through technical direction, design reviews, and code review; setting technical direction for your team's stack area; translating product requirements into scoped technical work and communicating trade-offs; working with bring-up teams to surface operational pain points and build scalable features; collaborating with security engineering on platform-layer security integration; coordinating with other platform leads on shared architecture and cross-team initiatives; owning reliability, observability, security, and interface standards; taking on complex engineering work directly; running post-mortems after incidents; and managing team operations including 1:1s, performance conversations, hiring, and onboarding.
Required qualifications: 5+ years in cloud platform or infrastructure engineering with at least 2 years leading an engineering team; strong backend or systems programming in production (Python, Go, Rust, or similar); deep Kubernetes knowledge including cluster operations, CNI networking, scheduling, and workload management; GPU infrastructure experience with provisioning and resource allocation; solid networking fundamentals (L2/L3, VLANs, overlay networks, multi-tenant isolation); service architecture skills for production control-plane services and APIs; security awareness around trust boundaries and least privilege; proven people management experience; and clear communication skills for technical and non-technical stakeholders.
Nice-to-have skills include: AI-assisted development and agent-assisted workflows; confidential computing technologies (TEEs, AMD SEV, Intel TDX); SaaS/PaaS layer experience; RDMA/InfiniBand/RoCE networking; distributed team experience; and serverless or inference serving infrastructure exposure.
