Program Manager managing AI acceleration chips and embedded systems product lifecycle. Leading technical execution and customer engagement in a hybrid work environment.
Responsibilities
Own and program manage all aspects of complex Software (SW) Releases, ensuring on-time delivery, quality, and scope adherence.
Drive and track progress across engineering and cross-functional teams, identifying bottlenecks, mitigating risks, and proactively driving execution to meet program milestones.
Champion and enforce effective program management methodologies and best practices across the organization.
Facilitate and drive alignment between engineering (SW, HW, Silicon), product management, sales, operations, and external partners.
Act as the primary point of contact for technical program matters with key customers, translating their needs into actionable engineering tasks.
Manage the funneling of requirements and defects back to the engineering organization, ensuring clear prioritization and timely resolution.
Clearly communicate program status, risks, and dependencies to executive leadership, technical teams, and external stakeholders.
Lead the end-to-end program management for safety certification processes (e.g., ISO 26262, IEC 61508) for our products and associated tools, ensuring all necessary documentation and engineering rigor is met.
Requirements
Minimum of 15+ years of progressive experience in a Program Management (PM) role, specifically focused on technical programs involving AI acceleration chips, embedded systems, software, and hardware.
Master's degree (MS) in Computer Science or a related technical field is required.
Proven experience successfully working with and managing distributed teams and programs across multiple geographies and timezones.
Deep expertise and proficiency with Program Management tools such as JIRA, GitHub Issues, and Quality Center (QC), including advanced reporting and workflow management.
Demonstrated ability to drive complex technical projects in the AI/ML and embedded processing domain.
Good understanding and working knowledge of AI SW compilers (e.g., TVM, MLIR, LLVM, IREE) (highly desired).
Knowledge of AI kernel development and familiarity with popular deep learning frameworks like JAX, PyTorch, ONNX, and TensorFlow (TF) (highly desired).
Current Program Management (PM) certification (e.g., PMP, PgMP, CSM, SAFe) is a significant plus.
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