Candidates with QA and release management experience in AI-driven engineering platforms will find this mid-level role at a fast-growing startup in Palo Alto.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Vinci4d via Ashby
ABOUT US
Vinci is building the intelligence layer for hardware engineering. For decades, physics has been one of the biggest constraints on how physical products get designed — not because engineers don't trust it, but because it's been too slow and too expensive to use continuously. Teams make hundreds of design decisions before they ever see high-fidelity physics; by the time the simulation arrives, the design is largely locked.
We change that. Our Foundation Model for Physics makes deterministic physical reasoning available while a design is still evolving, so engineers can make better decisions before the cost of change compounds. Unlike general-purpose AI, our model learns physical behavior from first principles — not from human-generated text or images.
Today, Vinci is deployed on production engineering programs at leading semiconductor companies — the hardest physics problems in modern electronics. Semiconductors are not the limit. They're the proof: our ambition includes everything downstream of the chip, from robots and vehicles to data centers and aircraft.
We're growing fast, and hiring across the company. Joining now means arriving early enough to help shape how Vinci works, not just what it ships.
GENERAL DESCRIPTION
As a Release Manager & QA Engineer at Vinci, you will be a primary guardian of our software’s reliability and conductor of our deployment cycles. Because our customers rely on us for critical engineering decisions, your role is pivotal in ensuring our predictions are accurate and our software is stable. Your core focus will be the verification and validation of our AI models and web platform. You will lead System Integration Test design and execution, eventually scaling these through automation, while championing Test-Driven Development across the engineering team. Additionally, you will orchestrate the ‘last mile’ of the delivery process to ensure seamless production releases.
THE ROLE
- Own the Release Lifecycle: Act as the final gatekeeper for production deployments, managing versioning, coordinating "Go/No-Go" decisions, and overseeing deployment pipelines and customer installations.
- Bridge Engineering & Product: Collaborate with AI/ML experts, thermal/mechanical engineers, and software developers to translate complex technical updates into actionable insights and release notes for both technical and non-technical customers.
- Architect Automated Test Suites: Design and maintain end-to-end automation frameworks (using Python and Playwright) that validate both our web interface and our underlying physics-AI inference engines.
- Validate Numerical Accuracy: Develop specialized testing strategies to compare Vinci’s AI-generated thermal and mechanical results against traditional FEA benchmarks, ensuring high-fidelity outputs.
QUALIFICATIONS
- Quality Expertise: 6+ years of experience in software quality engineering with a mastery of designing comprehensive test plans. You excel at defining the "what" and "how" of a test suite before any code is written.
- Test Architecture & Logic: The ability to translate complex engineering requirements into structured, unambiguous test logic. You can design clear procedural instructions that serve as a scalable blueprint for both manual execution and automation.
- The "Gatekeeper" Mindset: Exceptional attention to detail and the analytical ability to perform rigorous risk evaluations. You can weigh technical defects against deployment schedules to make informed "Go/No-Go" decisions during fast-paced release cycles.
- CI/CD & DevOps Literacy: Direct experience managing deployments within a Linux/Debian environment using tools such as GitHub Actions, Docker, or Jenkins.
BONUS QUALIFICATIONS
- Engineering Domain Knowledge: Familiarity with CAD/CAE data formats (GDSII, OASIS, STEP, ECXML, IPC) or basic concepts in thermal/mechanical simulation.
- HPC Experience: Background in testing high-performance computing applications or software that heavily utilizes GPU acceleration.
WHY JOIN US
- Be part of a team defining the future of AI in hardware design.
- Work at the intersection of advanced AI, real-world engineering, and customer success.
- Collaborate with world-class engineers and researchers in a fast-moving startup environment.
Source: Vinci4d careers (Ashby)