Senior Staff Engineer, Diagnostics and AI
Qualcomm
- Location
- San Diego, California, United States of America
- Work model
- On-Site
- Level
- Staff
- H-1B history
- 22 approvals (FY2023)
- Posted
- Sep 9, 2026
About this role
Company: Qualcomm Technologies, Inc. Job Area: Engineering Group, Engineering Group > ASICS Engineering General Summary: General Summary We are seeking a strategic, technically exceptional, and organizationally aware Senior Staff Engineer to help define the future of silicon Diagnostics, AI, and yield intelligence within Qualcomm's Yield Architecture and Engineering organization. This is an advanced research and development leadership role for an engineer who combines deep diagnostics expertise with systems thinking, AI innovation, and broad cross-functional influence. Qualcomm develops technologies across a wide range of products and emerging markets, including AI accelerator platforms, advanced 3D integration, system-technology co-optimization, automotive, robotics, and next-generation wireless systems such as 6G. The Product and Process Services organization works at the leading edge of these challenges, often before the problem, ownership model, data, or solution path is fully defined. This role will help turn those unknowns into new diagnostic architectures, intelligent engineering systems, and scalable technical capabilities. The charter is threefold. First, lead the architecture and evolution of silicon Diagnostics and yield intelligence for today's products and future technologies. Second, drive AI-enabled engineering transformation through practical applications of AI, agents, analytics, and automation. Third, provide strategic technical and organizational leadership by connecting Design, DFT, Product Engineering, Test Engineering, Failure Analysis, Yield Engineering, Automation, and AI teams around difficult cross-cutting problems and executable technical roadmaps. This is not a conventional Diagnostics management role. The successful candidate will operate as a research and development leader with a specialty in Diagnostics, using technical vision, architecture, influence, governance, and mentoring to shape capabilities across organizational boundaries. The role requires curiosity, sound judgment, organizational responsibility, and the ability to create structure and momentum where established methods do not yet exist. The Senior Staff Engineer will be based in the United States and will work closely with the Bangalore Diagnostics organization and its local leadership. This role provides global technical direction and cross-functional integration, while the Bangalore Director owns local organization building, talent development, operating discipline, and site execution.
Key Responsibilities
1. Diagnostics Architecture and Technical Strategy Define and evolve the architecture for Qualcomm's scan, memory, and emerging diagnostic capabilities. Connect readiness, execution, methodology, infrastructure, data, and learning across the silicon lifecycle while balancing immediate production requirements with long-term investment. 2. High-Volume, Production-Quality Diagnostics Provide technical leadership for reliable, scalable, high-volume, production-quality scan and memory diagnostics across Qualcomm's product portfolio. Establish standards and readiness criteria for quality, throughput, repeatability, and timely product enablement, and drive durable solutions to systemic gaps. 3. Advanced Technology and R&D Leadership Explore diagnostic and yield-intelligence approaches for advanced 3D integration, system-technology co-optimization, AI accelerator products, automotive platforms, robotics, and next-generation wireless systems. Anticipate how new architectures, packaging, workloads, and use conditions change observability, diagnosability, fault isolation, and learning. Convert uncertainty into research directions, prototypes, architectures, and scalable methods. 4. AI-Enabled Engineering Transformation Drive AI, agentic workflows, analytics, and automation across Diagnostics and adjacent yield workflows. Identify high-value problems where AI can accelerate analysis, improve signal detection, preserve knowledge, support