Software Engineer | Developer Experience

Volta•Palo Alto, CA

1d•$200,000 - $290,000

About The Position

Volta is building Kubernetes-native platforms for self-driving data centers, designed for near-total automation so AI compute can be secure, reliable, and scalable. As a Software Engineer on the new Developer Experience team, you will build tools, workflows, and agents that help engineers use AI across the product lifecycle. The work spans foundational development tooling—including development environments, CI/CD, and testing infrastructure—and AI-native capabilities such as MCP servers, coding agents, and evaluation systems. Success is measured by sustained adoption, faster feedback loops, higher-quality software, reduced toil, and more engineering work moving safely from intent to production. The role focuses on enabling engineers to work faster, with better quality and security.

Requirements

At least 4 years of experience in software, platform, infrastructure, AI, or developer tooling.
Experience making tooling secure by default, such as through supply-chain security, secrets management, and least-privilege access.
Experience building test clusters and cluster-management infrastructure to support developer environments.
Expert knowledge of state-of-the-art AI-assisted software engineering across harnesses, evaluations, verification loops, and observability.
Awareness of emerging industry learnings and a track record of responding quickly to promising innovations.
Judgment and discipline to balance exploration of emerging technology with exploitation of proven technologies.
Experience turning prototypes into reliable tools used by other engineers.

Responsibilities

Define and execute Volta’s developer experience roadmap for software engineering, including AI enablement.
Build the development platform, potentially spanning build systems, dependency management, and integration and test environments.
Work with state-of-the-art AI-assisted software engineering, including harnesses, evaluations, verification loops, and observability.
Integrate agentic workflows into developer environments, source control, CI/CD, observability, and incident-response systems.
Build agent infrastructure, including MCP servers, tool APIs, context and retrieval systems, permissions, auditability, and human approval paths.
Collaborate with Security Engineering to establish secure practices for governance, model access, and data handling.
Continuously improve the system based on engineer feedback.