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Disney Entertainment and ESPN Product & Technology

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.

Here are a few reasons why we think you’d love working here:

1. Building the future of Disney’s media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.

2. Reach, Scale & Impact: More than ever, Disney’s technology and products serve as a signature doorway for fans' connections with the company’s brands and stories. Disney+. Hulu. ESPN. ABC. ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally.

3. Innovation: We develop and implement groundbreaking products and techniques that shape industry norms and solve complex and distinctive technical problems.

Ad Platforms is responsible for Disney’s industry-leading ad technology and products – driving advertising performance, innovation, and value in Disney’s sports, news, and entertainment content, across all media platforms.

Job Summary

We are hiring a Staff Product Development Engineer to serve as the technical leader for AI Runtime & Reliability within Foundations Engineering – AI Production Engineering. This role partners closely with AI Core Engineering to ensure shared AI capabilities operate reliably, predictably, and at scale in production environments.

You will define and lead the architecture for AI runtime resilience, failover strategies, concurrency modeling, latency SLOs, and degradation patterns across AI-powered services. This role is deeply technical and system-oriented, with accountability for establishing production reliability standards for LLM-based systems and AI-driven workflows.

You will work cross-functionally with AI Core, Infrastructure, Security, Architecture and Product teams to harden AI systems before external or revenue-impacting scale.

Responsibilities:

Technical Leadership & Architecture

• Define reliability architecture standards for AI workloads across Ad Platforms.

• Establish latency SLOs and reliability targets for AI-dependent services.

• Design and implement circuit breakers, retry, fallback, and graceful degradation strategies.

• Lead multi-provider failover strategies across Azure, OpenAI, Bedrock, and future model providers.

• Define production readiness review standards for AI workloads.

Runtime & Scalability Engineering

• Lead concurrency modeling and throughput validation for model-dependent services.

• Design scalable backend services that support high-volume AI traffic.

• Partner with Infrastructure Engineering on capacity planning for AI workloads.

• Drive resilience testing and load validation prior to beta and production releases.

Operational Standards & Governance

• Establish AI production reliability best practices.

• Lead post-incident analysis for AI-related outages or degradations.

• Identify systemic reliability risks and drive architectural improvements.

• Partner with AI Core to ensure shared AI services meet enterprise production standards.

Engineering Excellence

• Contribute to critical reliability and runtime code paths.

• Mentor engineers on distributed systems and resilience patterns.

• Raise the bar for operational rigor and runtime reliability across the organization.

Basic Qualifications:

• 8+ years of backend software engineering experience building distributed systems at scale.

• Strong proficiency in Python (or similar backend language).

• Deep experience designing resilient microservices architectures.

• Strong understanding of retry semantics, circuit breakers, caching, and graceful degradation.

• Experience defining and enforcing service-level objectives (SLOs).

• Experience working with cloud environments such as AWS, Azure, or GCP.

• Proven ability to influence architectural decisions across multiple teams.

• Experience operating AI-powered or model-dependent services in production.

• Familiarity with LLM provider constraints (rate limits, latency variability, concurrency caps).

Preferred Qualifications:

• Experience designing multi-provider failover strategies.

• Background in high-throughput, low-latency service architectures.

• Experience participating in or leading incident response for distributed systems.

• Scalable distributed backend systems and microservices operating at high throughput.

Experience with:

• Designing and enforcing service-level objectives (SLOs) and reliability standards.

• Circuit breakers, retry semantics, graceful degradation, and resilience engineering patterns.

• Multi-provider integration strategies (e.g., Azure, OpenAI, Bedrock, external APIs).

• Concurrency modeling, rate limiting, and performance profiling.

• Observability systems including metrics, logging, tracing, and incident response workflows.

• Cloud-native architectures in AWS, Azure, or GCP environments.

• Production incident postmortems and systemic reliability improvement initiatives.

Required Education:

• Bachelor’s degree in Computer Science, Engineering, or related technical field (Master’s preferred), or equivalent experience.

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