Senior Manager Software Engineering

Disney · Media · Glendale, CA +2

Senior Engineering Manager to lead a software engineering team building and supporting ML-assisted content inspection pipelines within Disney's Content Platform Engineering organization. The role involves leading engineers in designing, implementing, and operating production systems that integrate LLMs and computer vision techniques for content automation, while also remaining involved in system design and architectural decisions. The manager will contribute to technical strategy, foster team development, and ensure alignment with product goals.

What you'd actually do

  1. Lead Software Engineering Efforts: Provide technical leadership for designing, implementing, and operating scalable distributed systems
  2. Manage and Develop Engineers: Lead, mentor, and develop a team of software engineers, setting clear expectations for technical ownership, delivery, and career growth.
  3. Own Delivery and Execution: Plan and deliver content initiatives by partnering with product stakeholders, managing scope and priorities, and ensuring high-quality measurable outcomes
  4. Drive Technical Collaboration and Alignment: Collaborate with adjacent engineering, ML, and platform teams to ensure consistent technical approaches, clear system boundaries, and effective integration of shared services

Skills

Required

  • 10+ years relevant industry experience
  • 3+ years managing a team
  • Proven track record of delivering complex software projects on time and within scope
  • Experience managing a team of software engineers
  • Strong problem-solving skills
  • Ability to communicate technical concepts clearly
  • Experience designing and building distributed systems, services, and APIs (REST and/or GraphQL)
  • Experience working with cloud platforms such as AWS and core services (e.g., S3, Lambda, EC2)
  • Experience operating and supporting production systems
  • Proficiency in at least one core programming language (e.g., Java, Python, or JavaScript)
  • Experience with containerization and orchestration tools such as Docker and Kubernetes
  • Knowledge of software engineering best practices, including testing frameworks, CI/CD pipelines, code reviews, and documentation standards

Nice to have

  • Experience integrating LLMs or other AI/ML inference services into production systems, including managing latency, reliability, and throughput.
  • Hands-on familiarity with computer vision pipelines or LLM-based workflows for content analysis, inspection, or validation.
  • Exposure to machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
  • Experience working within a media supply chain

What the JD emphasized

  • integrating LLMs or other AI/ML inference services into production systems
  • managing latency, reliability, and throughput
  • computer vision pipelines or LLM-based workflows for content analysis, inspection, or validation

Other signals

  • integrating LLMs
  • computer vision techniques
  • automate content inspection
  • production systems
  • distributed systems