Senior Director of Engineering - AI Platform

Qualcomm•San Diego, CA

10d•$281,600 - $422,400

About The Position

Qualcomm is seeking a visionary and execution-focused Senior Director of Engineering to lead AI for Snapdragon Compute platforms. This leader will define and drive Qualcomm's Compute AI software strategy across Snapdragon-powered Windows, Android, Linux PCs, enabling next-generation AI experiences and establishing Snapdragon as the premier platform for on-device AI computing. The successful candidate will lead a global organization responsible for AI systems, model enablement, NPU, GPU, CPU software integration, AI performance optimization, developer enablement, AI benchmarking, ecosystem partnerships, and joint engineering engagements with Microsoft, Google, OEMs, ISVs, and strategic technology partners. This role requires a unique combination of AI technical depth, platform systems expertise, and ecosystem influence to deliver industry-leading AI experiences spanning AI PCs, generative AI, multimodal AI, agentic AI, AI developer platforms, and future Snapdragon compute architectures. The role operates at the intersection of architecture, hardware, systems, software, AI algorithms, developer tools, and ecosystem enablement.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 10+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Master's degree in Computer Science, Engineering, Information Systems, or related field and 9+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
PhD in Computer Science, Engineering, Information Systems, or related field and 8+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Nice To Haves

Master's degree in Computer Science, Engineering, Information Systems, or related field.
5+ years of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras).
5+ years of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware.
5+ years of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media).
10+ years of experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++).
8+ years of experience using statistics and probability (e.g., conditional probability, Bayes rule).
8+ years in a technical leadership role with or without direct reports (only applies to positions with direct reports).
8+ years experience working in a large matrixed organization.
8+ years of work experience in a role requiring interaction with senior leadership (e.g., Vice President and above).
6+ years managing operating budgets and/or project financials.

Responsibilities

Define and execute Qualcomm's AI software strategy for Windows on Snapdragon platforms.
Drive creation of differentiated AI experiences leveraging Snapdragon CPUs, NPUs, GPUs, and heterogeneous compute architectures.
Influence future AI platform architecture requirements, software roadmaps, and ecosystem strategy.
Establish long-term technology direction for on-device AI, generative AI, large language models, multimodal AI, computer vision, and agentic AI workloads.
Partner with Compute, AI Software, System, Product Management, Customer Engineering, and Architecture teams to align investment priorities and execution plans.
Serve as engineering leader for strategic AI engagements with Microsoft.
Drive co-engineering activities across Windows AI, WinML, Windows AI Foundry, ONNX Runtime, Copilot+, and next-generation Windows AI capabilities.
Partner with Microsoft engineering organizations to define platform requirements, feature roadmaps, validation strategies, and performance targets.
Lead engagements with OEMs, commercial customers, independent software vendors, and open-source communities to expand the AI ecosystem on Snapdragon PCs.
Represent Qualcomm in executive-level technical discussions with strategic partners.
Lead teams responsible for end-to-end AI software enablement across Snapdragon compute products.
Drive optimization of AI workloads across NPU, GPU, CPU, and hybrid execution environments.
Oversee AI runtime integration, model deployment frameworks, developer tooling, and software release readiness.
Ensure successful enablement of emerging AI technologies and platform capabilities across current and future Snapdragon compute generations.
Guide platform-level analysis involving performance, power efficiency, memory utilization, concurrency, scalability, and user experience.
Drive onboarding, optimization, quantization, validation, and deployment of AI models on Snapdragon Compute platforms.
Lead development of model acceleration strategies for generative AI, vision models, language models, multimodal models, and emerging workloads.
Ensure world-class AI performance and efficiency through software and system optimization initiatives.
Partner with AI framework teams to address operator gaps, conversion challenges, runtime enhancements, and model portability requirements.
Define benchmarking strategy and performance targets for AI workloads.
Drive leadership results across industry benchmarks and customer-facing workloads.
Establish performance measurement methodologies and competitive analysis processes.
Lead optimization efforts required to achieve benchmark leadership across Snapdragon PC platforms.
Build, scale, and develop a high-performing global AI engineering organization.
Recruit and retain world-class talent across AI systems, machine learning, software engineering, performance engineering, and developer technologies.
Establish organizational structure, priorities, metrics, and execution frameworks.
Mentor directors, senior managers, architects, and technical leaders.
Foster a culture of innovation, accountability, technical excellence, and rapid execution.
Own execution of AI software deliverables across multiple Snapdragon Compute programs.
Manage cross-functional dependencies spanning silicon, firmware, drivers, AI runtimes, operating systems, developer tools, applications, and ecosystem partners.
Ensure timely delivery of AI features aligned with product milestones and customer commitments.
Drive issue resolution, risk management, quality initiatives, and operational excellence.