Senior Software Engineer

This technical role requires you to be in our Bay Area office in Atherton near Menlo Park.

The Role
You'll design, build, and ship core systems that power our AI platform. You'll work across the stack—backend services, infrastructure, APIs, and product features—and have real ownership over what you build. Expect to move between greenfield work and hardening existing systems, and to have your fingerprints on architecture decisions that matter.

About Voltai
Voltai is developing models and agents to evaluate, design, and interact with hardware and electronic systems.

The Team
We're hackers, researchers, and operators obsessed with building AI for electronic systems and semiconductors. Our team includes former Stanford professors, SAIL researchers, Olympiad medalists, and executives from Synopsys, GlobalFoundries, and Cadence. Despite the name drops, we care far more about execution than titles.

We're backed by Stanford, Sequoia, and leadership at Google, AMD, Broadcom and more. In other words, we have deep, deep access to the industry.

What You'll Do

• Ship features end-to-end working closely with research and product.

• Improve foundations: performance, reliability, observability, developer velocity.

• Raise the engineering bar through code review ad design discussions.

• Learn about hardware design. Previous experience is not expected, but you should be eager to familiarize yourself with how hardware is developed.

What We're Looking For

• 4+ years building production software. Internships and teaching assistantships don't count.

• Strong knowledge of agent development, evaluations

• Fluency in at least one backend language used in modern infrastructure (Python, Go, Rust, TypeScript, etc.)

• A track record of owning meaningful systems or features and not just contributing to them.
  

Bonus Points For

• Experience in EDA, semiconductor, or hardware-adjacent software environments

• Prior field engineering, solutions engineering, or customer-facing technical roles

• Background in ML infrastructure, model training, or model serving

• Experience at an early-stage startup where you wore multiple hats

Our AI Bullshit Meter

We are very good at catching people who use AI to exaggerate their abilities whether on paper or during interviews. Please don't waste our time.