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Voltai

AI world models for chip design & manufacturing

Senior Software Engineer: Integrations

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • At least 5 years of experience in backend engineering, full-stack development, or infrastructure/DevOps; internships and teaching assistantships do not count.
  • Familiarity with agent development and retrieval-augmented generation.
  • Strong systems design and debugging abilities.
  • Comfort with the Docker ecosystem, cloud infrastructure including Amazon Web Services, Microsoft Azure, and Google Cloud Platform, and infrastructure-as-code tools.
  • Openness to travel, mostly in California.

Responsibilities

  • Own customer deployments at offices across the San Francisco Bay Area, Cupertino, and Santa Clara.
  • Develop features specific to customer workflows and port features from the cloud product to on-premises environments inside highly restricted infrastructure.
  • Manage cloud deployments across Amazon Web Services, Microsoft Azure, Google Cloud Platform, and OpenShift, including provisioning, maintenance, and debugging.
  • Learn how hardware is developed at a high level.

Desired Qualifications

  • Experience deploying software on-premises in enterprise or air-gapped environments.
  • Prior field engineering, solutions engineering, or customer-facing technical experience.
  • Experience in electronic design automation, semiconductor, or hardware-adjacent software environments.

About the Company

Voltai

AI world models for chip design & manufacturing

Voltai builds AI models and agents that learn, plan, and experiment in the physical world, starting with semiconductor design and manufacturing. Its world models run virtual experiments, then validate results in real fabrication settings to build rich datasets across the hardware stack. What sets Voltai apart is a team of Stanford researchers, former chip-industry CTOs, and policy veterans working with major semiconductor, electronics, and automotive manufacturers. The goal is to speed hardware innovation through AI-driven simulation and validation.

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