Overview In this role you will define and advance validation strategy and coverage for Micron's Data Center SSD portfolio. You'll collaborate with architecture, firmware, and validation teams to translate requirements into actionable validation plans and reusable coverage models. You'll push AI-assisted approaches (Generative AI, LLMs) to improve requirements understanding, coverage analysis, and engineering productivity. This position offers impact across next gen storage technologies and a chance to shape validation practices at scale.
Compensation / Benefits- medical, dental and vision plans
- paid time-off
- paid holidays
Responsibilities- Define validation strategies and coverage architectures for next-gen Data Center SSD technologies
- Develop scalable validation methodologies to improve coverage quality and risk assessment
- Derive validation requirements from customer specs and architecture designs
- Lead coverage assessments and identify validation gaps
- Develop customer use-case-driven validation models and workload characterization
- Drive next-gen validation initiatives through technology evaluation and PoC development
- Apply AI-assisted techniques and LLMs to validation planning and requirements analysis
- Collaborate across engineering to align validation with product risk and business priorities
- Present technical recommendations to engineering and executives
- Mentor engineers and provide technical leadership across validation teams
Key requirements- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, Data Science, or related field
- 8+ years in Data Center SSD, storage systems, firmware, validation, or related disciplines
- Strong understanding of DC SSD architecture, NAND tech, storage protocols, firmware algorithms, enterprise storage
- Proven experience in developing validation strategies, qualification methodologies, or validation architectures
- Ability to analyze complex requirements and translate to validation approaches
- Experience with data analytics, automation, AI-assisted tools, or ML techniques
- Strong technical communication, leadership, and cross-functional collaboration skills
- Proven ability to drive technical initiatives across multiple engineering organizations
- technical leadership
- cross-functional collaboration
- clear communication
- AI-assisted tools and automation
- Generative AI and LLM usage in validation
- data analytics for validation and failure analysis
