VP, Engineering
$275,000–$310,000 year
On-siteSan Francisco, California, United States
Job Summary
Define the multi-year technical and AI strategy across the product ecosystem, championing new technologies to drive continuous improvement. Build AI-powered customer-facing capabilities including artist insights, content recommendations, and automated marketing while delivering measurable gains in delivery speed and quality through code generation and automated testing. Create and scale the paved path for agentic software development by establishing methodology, tooling, and safety frameworks, then drive adoption across the engineering organization. Lead, mentor, and develop an engineering organization of 25+ engineers, ensuring predictable execution and high-quality delivery across web, mobile, and internal platforms. Partner with Product, Design, and executive stakeholders to translate business goals into actionable technical plans.
Required Qualifications
- 12+ years engineering experience
- 5+ years leading orgs of 25+ engineers
- Proven success as a senior engineering leader at a scaled B2C, marketplace, or subscription-driven technology company
- Strong technical background with the ability to dive deep into systems architecture, data modeling, mobile performance, and platform-scale challenges
- Demonstrated experience deploying AI/ML in both customer-facing features and internal engineering workflows
- Track record of improving engineering velocity and developer experience through tooling, process, and automation
- Direct, hands-on experience building agentic-development capabilities from the ground up (must-have)
- Exceptional communication skills and experience partnering with product and executive leadership
Desired Qualifications
- Experience with large-scale content distribution, media ingestion pipelines, payments, subscription systems, or rights management
- Familiarity with Python/Django, JavaScript/TypeScript, Kubernetes, event-driven architecture, or modern mobile frameworks
- Strong understanding of data science, ML infrastructure, and experimentation platforms
- Background in creator economy, digital media, or marketplace ecosystems
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