Staff Engineer, AI Platform Enablement and Emerging Applications
samsungsemiconductor · San Jose, California, United States
- Location
- San Jose, California, United States
- Salary
- $163,000 - $253,000 USD
- Experience
- 10+ years
- Funding
- N/A
- Posted
- Sep 15, 2026
samsungsemiconductor is hiring a Staff Engineer, AI Platform Enablement and Emerging Applications based in San Jose, California, United States. Every apply link on Engg.space goes straight to the company's own careers page - no recruiter middleman, no generic job-board form.
Apply directly at samsungsemiconductorRole details
Please Note: To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period. Advancing the World’s Technology Together Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you’ll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what’s possible and powering the future. We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We’re dedicated to empowering people to be their true selves. Together, we’re building a better tomorrow for our employees, customers, partners, and communities. Samsung Semiconductor is hiring for an AI Platform Enablement & Emerging Applications Engineer that will lead SSD enablement activities for next-generation AI and compute platforms from major industry partners such as NVIDIA and AMD. This role will own end-to-end platform engagement, including early sample planning, SSD qualification, system validation, issue resolution, and production readiness for new platform launches. As AI infrastructure platforms continue to increase in scale and complexity, the engineer will coordinate closely with customer engineering teams and internal product, firmware, hardware, and validation organizations to ensure successful and timely SSD integration. In addition, the role will identify and incubate emerging AI storage applications and use cases, translating early customer and ecosystem signals into technical evaluations, proof-of-concepts, and future product opportunities. Location: Daily onsite presence at our San Jose headquarters in alignment with our Flexible Work policy with 10% of domestic travel. Reports to: Principal Engineer, R&D Product Development Planning What You’ll Do AI Platform Enablement: Lead SSD enablement and qualification activities for next-generation NVIDIA, AMD, and other strategic AI/compute platforms from early engineering engagement through production readiness. NPI Execution: Own SSD sample planning, allocation, qualification schedules, validation milestones, issue tracking, and launch readiness for major platform NPI programs. Customer Technical Engagement: Serve as the primary technical interface for platform qualification and integration activities, working directly with customer engineering and validation teams. System Validation & Issue Resolution: Coordinate system-level testing and drive cross-functional resolution of SSD, PCIe/NVMe, firmware, thermal, power, performance, and interoperability issues identified during platform qualification. Internal Program Coordination: Align product planning, firmware, controller, hardware, validation, quality, FAE, and operations teams to ensure timely delivery of samples, fixes, and qualification requirements. Platform Requirement Management: Capture and communicate platform-specific requirements, validation criteria, design constraints, and qualification feedback to internal product and engineering organizations. Emerging Application Incubation: Identify emerging AI storage workloads and applications, evaluate their technical requirements, and drive early feasibility studies, benchmarking, and proof-of-concept activities. New Opportunity Development: Explore new storage opportunities related to AI inference, KV cache and context storage, memory extension, checkpointing, GPU-direct I/O, agentic AI, and other emerging data-intensive workloads. Competitive & Ecosystem Analysis: Monitor AI platform evolution, storage architectures, competitor activities, and ecosystem trends to identify potential technology gaps and new product opportunities. Executive & Program Reporting: Provide clear visibility into platform status, qualification risks, technical issues, customer requirements, and emerging opportunities to internal leadership and cross-functional stakeholders. What You Bring Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a related technical field with 10+ years experience or a Master’s degree with 8+ years experience or a PhD with 5+ years experience. Minimum of 5+ years of experience in enterprise SSD, server platform, storage system, semiconductor, or data center infrastructure engineering. Platform Qualification Experience: Demonstrated experience supporting server, accelerator, or data center platform qualification and NPI programs, including sample management, validation planning, issue tracking, and production readiness. Storage & Interface Knowledge: Strong technical understanding of enterprise SSDs, PCIe, NVMe, server architecture, firmware, performance, power, thermal behavior, and system-level interoperability. AI/Data Center Familiarity: Working knowledge of modern AI and hyperscale infrastructure, including GPU-based systems, high-performance networking, PCIe switches/retimers, local NVMe storage, and large-scale server deployments. System Debugging Experience: Proven ability to investigate and coordinate resolution of complex system-level issues across hardware, firmware, software, and platform boundaries. Cross-Functional Program Experience: Experience working across engineering, product planning, validation, quality, operations, sales, FAE, and customer organizations. Communication Skills: Strong written and verbal English communication skills with the ability to communicate technical issues, program status, and recommendations effectively across global teams. Travel: Ability to travel as needed for customer engagements, platform bring-up, qualification activities, and industry events. Key Competencies Execution Ownership: Ability to independently drive complex platform enablement programs from early engagement through qualification and production readiness. System-Level Thinking: Ability to understand SSD behavior within the broader CPU/GPU, PCIe,
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