Sr. Director, Engineering

Key Responsibilities 

• Serve as the software technical leader for Qualcomm's next generation AI accelerator platform. 

• Define and execute the current Datacenter software vision, architecture, roadmap, and delivery strategy aligned with product and business objectives for the new AI accelerator 

• Lead multiple engineering organizations responsible for:  

• System software and firmware design and development. 

• Device drivers and kernel integration 

• AI runtimes and execution engines with emphasis on graphs spanning multiple NPU. 

• Compiler technologies and graph optimization 

• ML frameworks and ecosystem enablement 

• Platform SDKs, APIs, tools, profiling, and debugging solutions 

• Performance optimization and benchmarking 

• Validation, quality, and release engineering 

• Partner with silicon architecture and hardware engineering teams to co-design hardware and software features that maximize AI performance, efficiency, programmability, and scalability. 

• Drive software readiness across all chip development milestones, including architecture definition, emulation, pre-silicon enablement, bring-up, validation, customer engagements, and production release. 

• Establish performance, power, reliability, and usability goals for the platform software stack. 

• Lead strategic engagements with key customers, hyperscalers, ecosystem partners and standards organizations. 

• Build, mentor, and scale high-performing engineering teams across multiple geographic locations. 

• Foster a culture of technical excellence, innovation, accountability, collaboration, and operational rigor. 

• Present program status, technical strategy, and key decisions to executive leadership. 

Desired Qualifications 

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field. 

• 15+ years of software engineering experience, including significant leadership responsibilities. 

• 8+ years of experience leading large, globally distributed engineering organizations. 

• Experience delivering software platforms for complex SoC, accelerator, GPU, NPU, CPU, DSP, datacenter, or high-performance computing products. 

• Deep expertise in one or more of the following:  

• AI/ML software stacks 

• Compiler technologies 

• Runtime systems 

• Operating systems 

• Distributed computing 

• High-performance computing 

• Heterogeneous computing architectures 

• Demonstrated success driving cross-functional execution involving hardware and software co-development. 

• Strong understanding of modern AI workloads in particular inference for large language models/serving frameworks, multimodal AI, recommendation systems, and generative AI applications. 

Preferred Qualifications 

• Advanced degree (MS or PhD) in Computer Science, Electrical Engineering, AI/ML, or related discipline. 

• Experience leading software development for AI accelerators, GPUs, NPUs, TPUs, or custom silicon platforms. 

• Expertise in compiler technologies such as MLIR, LLVM or similar frameworks. 

• Experience with AI frameworks including PyTorch, TensorFlow, JAX, ONNX, Mojo, Triton or equivalent ecosystems. 

• Strong understanding of accelerator memory hierarchies, interconnects, parallel programming models, and performance optimization. 

• Expertise in compiler technologies such as Triton, MLIR, LLVM or similar frameworks 

• Experience supporting hyperscale cloud deployments and enterprise AI infrastructure. 

• Track record of delivering industry-leading developer platforms and software ecosystems. 

• Publications, patents, or recognized technical leadership in AI systems or high-performance computing. 

Leadership Characteristics 

• Visionary technology leader with the ability to define and execute transformative platform strategies. 

• Exceptional communicator capable of influencing executive stakeholders, customers, and engineering teams. 

• Strong systems thinker who can balance technical innovation, customer needs, and business priorities. 

• Proven ability to attract, develop, and retain world-class engineering talent. 

• Demonstrated ability to lead through ambiguity and deliver results in highly complex environments.