VP Software Engineering

Disney Disney · Media · Glendale, CA +1

VP of Software Engineering for Addressable Advertising, leading end-to-end engineering strategy, architecture, and execution of ad platforms. Oversees ad decisioning, insertion, measurement, optimization, and high-scale delivery systems for streaming monetization. Manages engineering organizations, develops technology roadmaps, and partners with Product, Data Science, and ad-tech providers.

What you'd actually do

  1. Establish and drive the long‑term engineering strategy for addressable advertising across all streaming brands.
  2. Lead, scale, and mentor high‑performing engineering teams responsible for ad‑delivery platforms.
  3. Develop the multi‑year technology roadmap for addressable advertising, aligned to business and monetization goals.
  4. Represent engineering in cross‑functional executive forums with Product, Data, Sales, Finance, and Operations.
  5. Drive technical standards, platform reliability, and engineering excellence across teams.

Skills

Required

  • Software engineering leadership
  • Large-scale distributed systems
  • Advertising technology
  • Ad decisioning
  • Ad serving
  • Streaming ad insertion
  • Measurement
  • Targeting
  • Managing senior engineering leaders
  • Multi-team organizations
  • Consumer or media systems delivery

Nice to have

  • Executive experience in streaming, digital advertising, or media platform
  • Machine learning for targeting, optimization, or relevance
  • AI adoption tracking
  • AI productivity improvement measurement
  • Training on advanced prompting techniques
  • Building systems for AI context provision
  • High-availability video streaming platforms

What the JD emphasized

  • 15+ years in software engineering
  • Expertise in advertising technology (ad decisioning, ad serving, streaming ad insertion, measurement, targeting)
  • Demonstrated experience managing senior engineering leaders and multi-team organizations
  • Proven track record delivering highly scaled consumer or media systems
  • Experience with machine learning for targeting, optimization, or relevance systems
  • Experience tracking AI adoption and measuring productivity improvements while ensuring quality metrics do not degrade
  • Proven capability to lead cultural change by providing training on advanced prompting techniques (e.g., meta-prompting, chain-of-thought) to move teams from basic to expert AI usage
  • Experience building systems that provide AI with necessary context, such as repository structure, coding standards, and documentation to generate relevant, accurate code