Software Engineer II

The Walt Disney Company • Glendale, CA

5d • Hybrid

About The Position

Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally. The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world. Product Engineering is a unified team responsible for the engineering of Disney Entertainment & ESPN digital and streaming products and platforms. This includes product engineering, media engineering, quality assurance, engineering behind personalization, commerce, lifecycle, and identity. The Observability & Insights group ensures that Disney Streaming’s distributed systems are reliable, performant, and transparent. We build the telemetry, dashboards, alerting, insights pipelines, and developer experience tooling that enable engineers across the organization to understand system health and take action quickly.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience
• 3+ years of applicable experience in backend development, including building AI-powered or data driven applications and scalable APIs (e.g. FastAPI, Flask)
• Practical experience in AI/ML engineering, with knowledge in at least one of the following areas: Agentic Workflows: Orchestrating foundation models (GPT-4, Claude) using frameworks like LangChain or LangGraph. Traditional ML: Developing, training, or fine-tuning models using frameworks like PyTorch or TensorFlow.
• Proficiency with AI-assisted development tools (e.g., Cursor, Claude Code) to accelerate engineering velocity.
• Experience with modern development practices, including version control (GitHub), containerization (Docker), and cloud-native deployments (AWS/EKS).
• Strong understanding of API design, microservices architecture, and standard SDLC workflows.
• Experience with modern development practices, including version control (GitHub), containerization (Docker), and cloud-native deployments (e.g AWS/EKS).
• Strong analytical and technical skills to troubleshoot issues, perform rapid iteration and quickly come-up with the possible solutions,
• Strong collaboration and communication skills, with the ability to work cross-functionally and clearly explain complex technical concepts

Nice To Haves

• Experience with observability platforms (e.g., Datadog, Grafana, Conviva) and handling high-volume telemetry data.
• Familiarity with large-scale data platforms and distributed data processing tools (e.g., PySpark, Pandas, Databricks, Snowflake).
• Knowledge of prompt design, model evaluation, and fine-tuning foundation models (GPT-4, Claude).
• Experience implementing production-grade systems at scale within a fast-paced, distributed environment.

Responsibilities

• Design and operate intelligent, production-grade systems that leverage real-time signals and AI-driven detection to improve the health of streaming platforms, critical services, and customer experience
• Build and scale AI-driven capabilities including agentic AI systems powered by modern foundation models (e.g. Claude Opus/Sonnet, GPT-4) enabling automated reasoning and decisioning, as well as predictive modeling and anomaly detection for real-time system health and reliability
• Develop end-to-end data and decisioning pipelines that transform telemetry, logs, and user signals into actionable insights, automated detection, and root cause analysis
• Create and deploy scalable APIs and services that deliver predictive signals, explainability, and insights to engineering teams, operational tools, and product stakeholders
• Partner cross-functionally to embed intelligence into workflows (incident response, release validation, customer insights), improving speed and reducing operational overhead
• Drive innovation in observability, reliability, and developer productivity through applied AI and new approaches

Benefits

• A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level