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Disney Entertainment and ESPN Product & Technology

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, you will design and build intelligent, AI driven systems that enhance the reliability and compliance posture of Disney's large-scale streaming infrastructure. You will develop agentic systems, machine learning models, and real-time automation that transform telemetry, logs, and infrastructure signals into automated detection, root cause analysis, and proactive policy enforcement and insights. 

In this role, you will contribute to the development of autonomous agents capable of reasoning over complex system behavior, identifying issues in real time, and driving faster detection and resolution across Disney+, Hulu, and ESPN. You will also contribute to systems that provide infrastructure visibility across a variety of Disney products, enforce compliance through preventative guardrails, correlate services to incidents for faster resolution, and quantify the impact of AI-driven observability tools on operational outcomes. You will partner closely with engineering, product, and platform teams to embed intelligence directly into operational workflows, improving system resilience and compliance posture at scale. 

As a Software Engineer II, you will deliver high quality features end-to-end, contribute to system design and architecture reviews, and begin owning components of production systems within a fast-paced, AI-native SRE engineering 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
• Contribute to infrastructure visibility and compliance enforcement systems that aggregate resource data across Disney products, enable ownership-scoped querying, and prevent non-compliant deployments
• 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

Basic Qualifications

• 3+ years of applicable experience in backend development, including building AI-powered or data driven applications and scalable APIs (e.g. FastAPI, Flask)
• Knowledge of AWS services and cloud architecture to inform what infrastructure characteristics should be measured and evaluated for reliability and compliance
• 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.
• 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

Preferred Qualifications 

• 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.

Education

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience

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