Chief of Staff to SVP, Engineering Lead - Data Center (Senior Director)

Qualcomm•San Diego, CA

16d•$220,000 - $330,000

About The Position

The Chief of Staff will serve as a strategic and operational partner to the SVP BU Engineering Lead for Data Center BU Engineering. This role will help drive execution across Data Center AI, CPU, custom silicon, networking, hardware systems, and global engineering priorities. Guided and empowered by the SVP BU Engineering Lead, the Chief of Staff will manage operating cadence, coordinate cross-functional execution, improve decision velocity, and ensure clear alignment across engineering, product, program management, finance, operations, talent acquisition, and executive stakeholders. Prior experience serving in a Chief of Staff or equivalent executive operations capacity is preferred, particularly in complex engineering, semiconductor, AI, cloud, or data center environments.

Requirements

Bachelor's degree in Business Administration, Engineering, Finance, Marketing, or related field and 12+ years of business operations or related experience.
Associate's degree in Business Administration, Engineering, Finance, Marketing, or related field and 14+ years of business operations or related experience.

Nice To Haves

Master's degree in Engineering, Business Administration, Finance, Operations, or related field.
15+ years of experience in engineering operations, strategy, product/program execution, or business operations within semiconductor, cloud, AI, data center, or infrastructure environments.
Prior experience as Chief of Staff, business operations leader, or executive operations partner supporting an SVP/GM-level engineering or business leader is strongly preferred.
Strong technical and business acumen with the ability to operate across AI hardware, software platforms, CPU, networking, custom silicon, hardware systems, and customer-facing engineering priorities.
Demonstrated ability to influence senior leaders, drive clarity in ambiguity, manage executive communications, and deliver results in a fast-moving, matrixed global organization.

Responsibilities

Partner with the SVP BU Engineering Lead and the Data Center BU Engineering leadership team to define, prioritize, and execute strategic initiatives across AI inference processors, AI software enablement, server CPU, custom silicon, networking, hardware systems, and rack-scale engineering.
Drive the operating rhythm for the organization, including leadership reviews, execution tracking, staffing priorities, roadmap alignment, budget visibility, and follow-through on critical decisions. Navigate complex matrix structures and influence across engineering, product, finance, HR, operations, and executive teams.
Act as a trusted point of coordination between the SVP BU Engineering Lead, Data Center BU Engineering leaders, peer organizations, and key stakeholders. Prepare executive-ready communications, leadership updates, decision briefs, organizational messages, and follow-up action plans.
Lead high-priority cross-functional initiatives from concept through execution, including engineering buildout plans, leadership hiring priorities, AI300 readiness, hardware systems scale-up, and process improvements that increase organizational speed and accountability.
Establish and manage key performance indicators, dashboards, and reporting mechanisms to track hiring, program execution, engineering milestones, budget, risks, and organizational capacity.
Identify execution gaps, organizational bottlenecks, and decision blockers; develop practical options, escalate appropriately, and drive closure with clear ownership and timelines.
Shape agendas, materials, and follow-through for key leadership forums, staff meetings, operating reviews, customer-facing discussions, and executive updates to ensure meetings are focused, decision-oriented, and productive.
Coordinate with the SVP BU Engineering Lead’s administrative support and leadership team to prioritize executive meetings, customer engagements, travel, internal reviews, and stakeholder follow-ups.
Evaluate risks across roadmap execution, staffing, customer commitments, organizational scale, and cross-functional dependencies; provide recommendations that enable timely and informed decisions.