Software Test Manager, AI Systems

Key Responsibilities

Test Strategy & Execution Leadership

• Define, implement, and lead the overall test strategy for the AI software stack, covering the entire end-to-end pipeline from compiler to hardware execution.
• Establish and drive a robust testing framework that includes unit testing, functional testing, component testing, and system-level testing.
• Oversee the continuous integration and continuous delivery (CI/CD) quality gate processes.

Safety, Certification & Compliance

• Manage and lead all testing activities required for FUSA/ISO 26262 certification, ensuring the functional safety of the delivered software components.
• Develop and maintain a system for traceability of the solution from requirements through architecture, design, and testing artifacts.

Team & Management

• Lead, mentor, and manage a team of quality assurance and test engineers.
• Effectively manage managed services and/or contractors to augment internal testing capacity and specialized needs.
• Serve as the primary liaison between the development, product, and safety teams regarding quality metrics and release readiness.

Tools & Process

• Drive the effective use of JIRA/Github issues for all issue tracking and defect management.
• Implement and leverage AI tools and methodologies for testing purposes to enhance automation, coverage, and efficiency.

Requirements

• 5+ years of hands-on experience in a Software Test Management or Quality Assurance leadership role, specifically within an embedded, compiler, or AI/ML software domain.
• Deep expertise in developing and managing comprehensive test plans for complex software systems (e.g., compilers, operating systems, hardware interfaces).
• Proven experience with rigorous industry quality standards, including leading testing efforts for FUSA/ISO 26262 or similar safety-critical standards.
• Expert-level knowledge and practical experience with JIRA/Github issues for managing the full lifecycle of issues, defects, and establishing requirements traceability.
• Demonstrated experience managing both internal teams and external resources (e.g., contractors, managed services).
• Familiarity with the architecture of graph compilers, LLVM, or other toolchains relevant to AI/ML acceleration.

Preferred Qualifications

• A Master's degree in Computer Science, Embedded Systems, Artificial Intelligence, or a related technical field.
• Direct experience with AI tools used for enhancing testing, such as machine learning for test case generation, anomaly detection in logs, or predictive defect modeling.
• Experience in the automotive or high-reliability embedded computing industry.
• Familiarity with various programming languages relevant to the stack (e.g., C++, Python).

Benefits

• Competitive salary and meaningful equity
• Medical, dental, and vision coverage starting on day one
• 401(k) retirement plan
• Flexible paid time off (unlimited, non-accrual)
• Company-provided lunches and stocked kitchen (in-office)
• Support for commuting, including monthly parking or Caltrain passes