Description
We are seeking a dedicated and highly analytical Software Product Engineer to join our team, focusing on our cutting-edge Android Automotive OS application. This critical role involves ensuring the stability, reliability, and performance of a complex hybrid embedded & cloud system.
The ideal candidate will be instrumental in identifying, analysing, and driving the resolution of critical issues, enhancing our quality processes, and contributing to a robust failure mode avoidance strategy. This is a hands-on role that requires deep technical expertise, exceptional problem-solving skills, and a proactive approach to quality improvement.
Responsibilities:
- Lead the triage of reported issues within the BluAI In-Vehicle application and its associated cloud components.
- Conduct thorough and systematic root cause analysis for complex software failures, presenting detailed findings and actionable recommendations to development and cloud teams during daily review meetings.
- Collaborate with the Software Product Engineers (SPEs) to proactively identify potential failure modes for new features through comprehensive Design Failure Mode and Effects Analysis (DFMEA).
- Ensure that identified failure modes are adequately addressed through robust test case development and alignment with overall test strategies.
- Review and critically analyse QA test reports and results to identify patterns, critical defects, and areas for test process optimisation.
- Partner closely with the QA team to refine test cases, establish clear preconditions, and define precise acceptance criteria to enhance the effectiveness of validation efforts.
- Maintain and update critical quality documentation, including DFMEA records, issue tracking systems, and quality history.
- Drive the creation of new test cases based on identified regressions, previously untested failure modes, and evolving product requirements to continuously improve test coverage.
Qualifications:
- Proven working knowledge and practical experience with the Android Automotive OS ecosystem and its core components.
- Demonstrated proficiency in system-level debugging for complex software, including expert analysis of verbose logcat output using command-line tools (e.g., ADB) and advanced code/text editors.
- A track record of successfully performing comprehensive root cause analysis for intricate software failures across embedded and cloud systems, with the ability to clearly articulate the diagnostic process and propose effective, long-term solutions.
- Solid understanding of asynchronous and concurrent processes, WebSocket cloud connectivity, WebRTC and applicable audio transmission protocols.
- Excellent verbal and written communication skills, with the ability to effectively collaborate with cross-functional teams (developers, QA, cloud engineers, SPEs) and present complex technical findings clearly and concisely.
- Familiarity with quality management systems and methodologies (e.g., Ford FMA, Quality History, Fish Bone Analysis, DFMEA, 8D/5D, Six Sigma).
- Proficiency with issue tracking tools (e.g., JIRA, Azure DevOps) and version control systems (e.g., Git).
Preferred qualifications include experience with automated testing frameworks and continuous integration/continuous deployment (CI/CD) pipelines, knowledge of voice assistant technologies, natural language processing (NLP), and speech recognition concepts.