Staff, Engineer – Product Stability Test (PDT)

Technology, Data & Digital · Software & Web Development · Software Engineering · QA & Testing

In short

We are looking for a Product Stability Test Lead to lead system-level stability validation, debugging, and commercialization readiness for next-generation SoC and software platforms. This role involves identifying, reproducing, triaging, and resolving complex hardware and software stability issues across various subsystems, requiring deep technical expertise and cross-functional leadership.

Responsibilities

Define and execute product stability strategies, test methodologies, and quality gates for successful commercialization.
Establish MTBF, reliability, and stability KPIs for complex SoC platforms and software products.
Provide technical leadership across multiple programs and product generations.
Drive system-level stability initiatives spanning Android, Linux, QNX, Hypervisor, and embedded software environments.
Lead large-scale stress, endurance, reliability, and concurrency testing across supported IPs and subsystems.
Design, review, and optimize stability test plans, scenarios, and automation frameworks.
Expand coverage for emerging technologies, new features, new chipsets, and customer use cases.
Ensure adequate validation coverage across lab, CI, and field environments.
Own critical system-level defects including system hangs, kernel panics, watchdog resets, memory corruptions, CPUSS failures, boot failures, performance degradations, and power/thermal anomalies.
Perform deep log analysis using crash dumps, traces, ramdumps, CoreSight, T32, crash utility, and internal debug tools.
Drive root cause identification and corrective actions in partnership with HW and SW technology teams.
Lead triage reviews and establish defect prioritization strategies.
Partner closely with Functional Test Teams, Development Teams, Platform Integration, Architecture Teams, Commercial Engineering, Customer Engineering, and Program Management.
Drive issue resolution across multiple organizations and geographic locations.
Represent Product Stability in executive reviews and customer readiness discussions.
Develop automation frameworks to improve stability testing efficiency, triage, and reporting.
Enable AI-assisted and data-driven approaches for defect identification and coverage optimization.
Build dashboards and metrics to monitor MTBF, stability escapes, defect aging, test effectiveness, and commercialization readiness.
Champion continuous improvement through automation and analytics.
Assess product readiness and provide recommendations for release decisions.
Analyze customer-reported issues and incorporate learnings into validation strategies.
Ensure field issues are reproduced, debugged, and resolved effectively.
Minimize stability escapes and ensure customer satisfaction.
Mentor engineers and technical leads on debugging methodologies and system architecture.
Drive knowledge sharing and debugging best practices across teams.
Influence technical direction and architectural improvements through data-driven insights.
Lead technical reviews and contribute to organizational strategy.

Requirements

Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related technical discipline.
10+ years of industry experience in software, systems, platform validation, or product stability.
Proven experience leading large-scale product stability efforts for complex systems.
Strong experience in Linux / Android / QNX internals.
Experience with embedded systems.
Experience with SoC architecture.
Experience with CPU, Memory, Interrupt and Scheduler subsystems.
Experience with Hypervisor and virtualization technologies.
Experience with Power management frameworks.
Experience with Device drivers and kernel debugging.
Experience with Reliability and stress testing.
Experience with Multi-core system architecture.
Experience with Crash analysis and root-cause debugging.
Experience with Performance and stability optimization.
Experience with crash dump analysis tools.
Experience with GDB / LLDB.
Experience with JTAG / T32.
Experience with CoreSight.
Experience with Kernel trace frameworks.
Experience with CI/CD systems.
Experience with Python automation.
Experience with Data analytics and dashboarding tools.
Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Software Engineering or related work experience.
OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Software Engineering or related work experience.
OR PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
3+ years of work experience with Programming Language such as C, C++, Java, Python, etc.

Desired Qualifications

Automotive, XR, Compute, Mobile, IoT, or Edge platform experience.
Experience with commercialization and customer-facing programs.
Experience building large automation and validation infrastructures.
Knowledge of functional safety (FuSa) and reliability engineering.
Publications, patents, or contributions to system architecture improvements.

Benefits

Qualcomm is an equal opportunity employer.
Qualcomm is committed to providing an accessible process for individuals with disabilities.
Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process.
Qualcomm is also committed to making our workplace accessible for individuals with disabilities.

Skills

LinuxAndroidQNXEmbedded systemsSoC architectureCPUMemoryHypervisorVirtualizationPower managementDevice driversKernel debuggingCrash dump analysisGDBLLDBJTAGT32CoreSightKernel traceCI/CDPythonData analyticsCC++Java

#software engineering#product stability#test lead#system-level validation#debugging#SoC#software platforms#hardware#CPU#GPU#Memory#Power#Connectivity#Multimedia#Virtualization#Automotive#Android#Linux#QNX#Hypervisor#embedded software#crash analysis#root cause analysis#automation#data analytics