Release Manager & QA Engineer

Vinci4D

$125K — $150K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 6+ years in software quality engineering with strong test plan design skills.
  • Ability to convert complex engineering requirements into clear test logic.
  • Keen attention to detail for comprehensive risk evaluations.
  • Experience with CI/CD processes in Linux/Debian using tools like GitHub Actions.
  • Proficient in Python and automation frameworks like Playwright.

Responsibilities

  • Manage the entire Release Lifecycle and oversee production deployments.
  • Collaborate with cross-functional teams to produce clear release notes.
  • Design and maintain automated test suites for web interfaces and AI inference models.
  • Develop strategies to validate AI-generated results against established benchmarks.
  • Champion Test-Driven Development practices across the engineering team.

Benefits

  • Be part of pioneering AI development in hardware design.
  • Engage in a dynamic startup atmosphere with leading engineering talent.
  • Participate in projects that blend cutting-edge AI with practical engineering challenges.
Full Job Description
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.

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