Senior Vice President, Software Engineering

Fanatics Commerce•Redwood City, CA

2d•$370,000 - $425,000•Hybrid

About The Position

Fanatics Commerce is seeking a Senior Vice President of Software Engineering to own and elevate the technology powering its ecommerce platform. The role leads an approximately 180-person Engineering and Business Intelligence organization through senior engineering leaders and is accountable for the quality, performance, and reliability of the fan-facing ecommerce experience. It calls for an executive leader with current technical judgment across modern front-end and distributed systems, experience scaling large engineering organizations, and the ability to lead during high-stakes production incidents. The position sets technical direction for the front-end stack and high-volume cloud services, advances marketing and customer data platforms, and drives reliability, security, engineering quality, and cost effectiveness. It also leads adoption of AI capabilities across engineering and customer experiences, partnering with Product, Marketing, Merchandising, Operations, and Data Science to deliver measurable business and fan outcomes. The role is based at the company's Redwood City, California office under its hybrid work policy, currently requiring in-office presence Tuesday through Thursday. The listed base salary range is $370,000–$425,000 USD; the range excludes short- and long-term incentive compensation.

Requirements

Demonstrated experience building, leading, and growing an internal engineering organization of comparable scale (approximately 180 people or more) through senior leaders; consulting or oversight experience alone does not meet the stated requirement.
Deep, current technical judgment in modern front-end stacks such as React/TypeScript or comparable technologies, including server/client rendering, CDN caching, accessibility, browser performance, and native-versus-web-versus-hybrid app trade-offs.
Experience owning the technology stack behind a very large-scale consumer experience.
Hands-on ownership of high-volume cloud production services and the ability to assess microservices architecture, API contracts, asynchronous messaging, caching, data consistency, idempotency, and latency, resilience, and cost trade-offs.
Proven experience scaling empowered agile teams and modern delivery practices, including CI/CD, automated testing, feature flags, and progressive rollout and rollback.
Experience deploying AI coding agents and assistants with training, review, testing, and data controls, with demonstrated gains in lead time and quality.
Executive incident leadership experience as a CEO/C-suite point of contact for time-critical production issues, including directing cross-team response, communicating business impact and recovery options, and driving root-cause fixes.
Ability to maintain credibility with senior engineers and executive stakeholders.
Strong partnership skills with Product, Marketing, Merchandising, and Operations, and a track record of translating business objectives into engineering strategy and measurable fan-facing outcomes.

Nice To Haves

Experience leading engineering for modern marketing platforms, including CRM and customer data platforms, is preferred but strongly valued.
Ability to partner with Data Science on ML-driven personalization and demonstrate measurable improvements in conversion, engagement, and retention through rigorous experimentation.

Responsibilities

Partner with Product, Marketing, Merchandising, and Operations to improve technology, identify innovation opportunities, and advance business objectives.
Communicate technical complexity and business impact clearly to senior engineers and executives, maintaining credibility and trust.
Act as the C-suite point of contact and executive incident commander for critical production incidents; direct response, communicate business impact and recovery options, and ensure root-cause fixes are completed.
Build, lead, and grow the senior engineering leadership team; oversee hiring, performance management, succession planning, and delivery accountability across an approximately 180-person organization.
Recruit, develop, and retain high-caliber engineering leaders and individual contributors while maintaining a high bar for technical excellence.
Scale empowered agile teams and modern delivery practices, including CI/CD, automated testing, feature flags, and progressive rollout and rollback.
Set and enforce front-end technical direction and quality standards for rendering strategy, CDN caching, accessibility, and browser performance; connect Core Web Vitals and real-user monitoring to conversion and customer experience.
Advance CRM, customer data, and real-time activation platforms, with strong data quality and governance, and partner with Data Science on personalization and measurable customer outcomes.
Own architecture and operational excellence for high-volume cloud production services, including microservices boundaries, API contracts, asynchronous messaging, caching, data consistency, and idempotency.
Establish service-level objectives, error budgets, observability, and on-call ownership to protect the fan experience during peak traffic.
Drive responsible adoption of AI coding agents and assistants through training, review, testing, and data controls, demonstrating gains in engineering lead time and quality.
Transform engineering processes to make effective use of AI capabilities and apply data and AI to improve marketing effectiveness, engagement, and growth.
Partner with Data Science on ML-driven personalization and use rigorous experimentation to improve conversion, engagement, and retention.
Pursue platform innovation, including applied AI for search and recommendations, checkout and payments, and developer self-service.
Improve cloud production reliability through load testing, autoscaling, and resilience practices, and quantify throughput, tail latency, availability, and recovery improvements.
Embed security in delivery, improve cloud unit economics, and oversee engineering quality, technical debt, and investment trade-offs.
Use AI and technology to improve efficiency, quality, and outcomes; use data and digital tools to inform decisions; and contribute to continuous innovation and improvement.