Software Quality Assurance Engineer

Mountain View, California, United States

Applied Intuition is the vehicle intelligence company that accelerates the global adoption of safe, AI‑driven machines. Founded in 2017 and now valued at $15 billion following its recent Series F funding round, Applied Intuition delivers the Vehicle OS, Self‑Driving System, and toolchain to help customers build intelligent vehicles and shorten time to market. 18 of the top 20 global automakers and major programs across the Department of Defense trust Applied Intuition’s solutions to deliver vehicle intelligence.

Applied Intuition services the automotive, defense, trucking, construction, mining, and agriculture industries and is headquartered in Mountain View, CA, with offices in Washington, D.C., San Diego, CA, Ft. Walton Beach, FL, Ann Arbor, MI, London, Stuttgart, Munich, Stockholm, Bangalore, Seoul, and Tokyo. Learn more at

We are an in‑office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments.

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Note:

For Epi Sci job openings, fully remote work will be considered by exception.)

We are seeking an experienced Software Quality Assurance Engineer to join our team. The ideal candidate will be responsible for ensuring the quality and reliability of software products used in automotive applications. This role involves developing test strategies, creating automated test frameworks, and collaborating with cross‑functional teams to improve software quality throughout the development lifecycle.

• Create and implement quality assurance strategy based on project scope.
• Collaborate closely with engineers on the design and validation of test planning, based on software requirements.
• Support the system and software engineering teams on test execution.
• Analyze test results, provide reports, and be responsible for critical performance of software feature releases and updates.
• Review and validate ongoing improvements of testing requirements.
• Support engineering team on the processing of nonconformities (bugs, failures, audit findings, etc.).
• Ensure traceability of overall quality assurance results (process confirmations, audits, KPIs).
• Work with the engineering team on streamlining test and test results process, implementing automated testing frameworks and tools to enhance testing efficiency and coverage.
• Conduct assessments and internal audits to ensure compliance with automotive industry standards (e.g., ISO 9001, Automotive SPICE, etc.).
• Participate in design reviews and provide feedback on software architecture and implementation.
• Implement and maintain an escalation mechanism.

• BS, MS, or PhD in Electrical Engineering, Computer Science, or other related fields.
• 3+ years of experience in automotive SW quality assurance/engineering.
• Understanding of programming languages such as C, C++, and Python, to be able to review, analyze, and contribute to technical discussions (no writing code experience required).
• Experience with automated testing tools and frameworks (e.g., GTEST, Pytest).
• Experience with international industry / models standards – ASPICE and ISO 9001:2015.
• Experience in conducting work product audits, process audits, according to ASPICE, process compliance with ISO
  9001:2015 and driving quality issues to closure.
• Experience with problem solving methodologies: knowledge and experience with 8D methodologies, in depth understanding of Root cause analysis methodologies.
• Well conversant with statistical charts and data interpretation.
• Experience in process documentation, and knowledge of process framework, hierarchy, guideline development.
• Preparation and presentation of SW product quality status including‑ SW product quality metrics, audit metrics, top quality issues and risks.

• Experience with model‑based…