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:
- 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.
- 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.
- Innovation: We develop and implement groundbreaking products and techniques that shape industry norms and solve complex and distinctive technical problems.
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.
Job Summary:
As a Software Engineer II on the Reliability Insights team, you will design and build data and reporting pipelines that evaluate and prove the real-world performance, precision, and business impact of Disney?s operational AI and observability tools. You will bridge backend engineering and data-driven insights, transforming raw telemetry, AI agent interactions, and operational logs into clear metrics around AI reliability, model drift, and incident mitigation.
In this role, you will build automated ground-truth pipelines and model evaluation frameworks that quantify how effectively AI agents and anomaly models perform in production. You will capture end user feedback, correlate AI signals with incident resolution timelines (e.g., Mean Time to Mitigation), and build single pane dashboards for engineering and leadership. Partnering closely with SRE, product, and platform engineering teams, you will eliminate visibility gaps, reduce alert noise, and establish clear standards for AI model performance across Disney+, Hulu, and ESPN.
Responsibilities:
- Design, build, and maintain automated feedback pipelines that capture operational outcomes (confirmed incidents, false positives, dismissed alerts) and correlate them directly back to AI model predictions and agent actions.
- Develop programmatic evaluation frameworks to track model precision, recall, and drift over time, establishing automated threshold alerts to proactively trigger model tuning and prevent alert fatigue.
- Build end-to-end data pipelines linking AI outputs to incident lifecycles, quantifying business impact through metrics such as Service to Incident correlation, notification success rates, and Mean Time to Mitigation (MTTM).
- Design and deploy scalable APIs, metrics layers, and single-pane model health dashboards that present clear AI ROI, operational health, and performance narratives to leadership and technical stakeholders.
- Build mechanisms to capture structured feedback from end users to continuously feed real-world usage signals back into model improvement cycles.
Basic Qualifications:
- 3+ years of applicable experience in backend and data pipeline engineering, including building scalable APIs (e.g., FastAPI, Flask) and metrics/insight generation platforms.
- Strong experience with data platform engineering and distributed processing tools (e.g., PySpark, SQL, Pandas, Databricks, Snowflake) to process and analyze telemetry data.
- Practical understanding of model evaluation concepts, such as precision, recall, model drift, and ground-truth labeling systems.
- Hands-on experience with modern development practices, including version control (GitHub), containerization (Docker), and cloud-native deployments (AWS/EKS).
- Proficiency with AI-assisted development tools (e.g., Cursor, Claude Code) to accelerate engineering velocity.
- Strong analytical skills to translate complex system telemetry and operational logs into meaningful reliability metrics and business insights.
- Excellent cross-functional collaboration and communication skills, with a track record of partnering with operational teams (SRE, DevOps) to turn raw data into actionable insights
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Preferred Qualifications:
- Experience with observability, telemetry, and monitoring platforms (e.g., Datadog, Grafana, Conviva).
- Familiarity with agentic workflows and foundation models (e.g., GPT-4, Claude) and how to evaluate their output accuracy.
- Knowledge of incident management workflows and SRE metrics (e.g., MTTR, MTTD, alert suppression).
- Prior experience working on data attribution, metrics aggregation, or financial/performance visibility tooling in high scale environments.
Required Education
- Bachelor?s degree in Computer Science, Engineering, or equivalent experience
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The hiring range for this position in New York, NY is $124,900.00 to $167,400.00 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate?s geographic region, job-related knowledge, skills, and experience among other factors. 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.
