Micron
Principal Engineer, Firmware & Product Test
$145K–$286K
Longmont-MAX- Office, CO +1 · Principal · Full-time · Posted Aug 24, 2026
- Location
- Longmont-MAX- Office, CO
San Jose, CA - Experience
- 10+ years with a bachelor’s degree, 8+ years with a master’s degree, or 6+ years with a PhD.
- Education
- Bachelor’s degree in Computer science, Electrical/Computer Engineering, or a related field; alternatively, a Master’s degree or PhD.
About the job
Lead firmware validation for enterprise SSD products by defining verification strategies, building test automation, and driving failure analysis across multiple programs.
What you'll do
- Lead test planning, automation, and coverage closure for NVMe front-end firmware features.
- Build and improve Python test frameworks, CI/CD integration, regression infrastructure, and reporting.
- Lead failure analysis; set validation standards, mentor engineers, and partner with firmware teams on testability and AI-enabled workflows.
What they ask for
- Bachelor’s degree in Computer science, Electrical/Computer Engineering, or a related field with 10+ years of relevant experience, or a Master’s degree with 8+ years, or a PhD with 6+ years.
- Expert-level Python programming and success building production-quality test automation frameworks.
- Experience validating NVMe front-end features, including SMART, Admin Commands, Namespace Management, and OCP functionality.
- Expertise in failure analysis, root-cause investigation, log analysis, defect documentation, test architecture, and validation methodologies.
Nice to have
- Knowledge of NVMe and PCIe protocols, enterprise SSD firmware architectures, NAND flash, FTL concepts, or storage validation.
- Proficiency in Rust or C; firmware debug tools, protocol analyzers, coyote event logs, Linux or Windows administration, Git, CI/CD, or AI tools such as Claude Code.
Pay
$145,000.00 - $286,000.00 a year (USD, base salary)
Tools
Python, NVMe, SMART, Admin Commands, Namespace Management, OCP, CI/CD, Claude Code
AI focus
Use AI-enabled workflows and engineering tools to improve efficiency; preferred applications include code creation or verification and AI/ML for test optimization, anomaly detection, or failure triage.
Model-written summary · the original posting is authoritative