Principal Software Engineer - Observability

Overview As a Principal Software Engineer, you will be a hands-on builder tackling unfamiliar codebases to accelerate AI-driven engineering velocity. You’ll design production-grade, intelligent systems that enhance the reliability of Disney’s large-scale streaming ecosystem and deploy autonomous agents that act on real-time telemetry. You’ll shape technical direction, optimize AI usage for cost and performance, and collaborate across teams to deliver measurable business value. This role offers the chance to lead AI-enabled observability and developer productivity efforts at scale. Compensation / Benefitsbonus and/or long-term incentive unitsmedical and other benefitscompetitive compensationopportunity to work on Disney brandsglobal impact ResponsibilitiesDesign and operate real-time, AI-powered systems to improve streaming health and customer experienceBuild fully autonomous agentic systems leveraging frontier models to reduce human interventionDevelop memory, prompting, context strategies, and orchestration patterns to maximize model accuracy and minimize hallucinationsCreate end-to-end data and decisioning pipelines and scalable APIs delivering insights to engineers and product stakeholdersOptimize AI usage through prompt optimization, caching, batching, and smart routing across models and infrastructuresMaintain production-grade software practices: tests, code reviews, CI/CD, and secure, reliable componentsRapidly onboard to new codebases and modernize them with AI, aligning work with business value and incident workflowsCollaborate cross-functionally to embed intelligence into workflows like incident response, release validation, and observability enhancements Key requirements10+ years of software engineering experienceExperience delivering AI-powered or data-driven applications and scalable APIsProven ability to ramp quickly on unfamiliar codebases and modernize systems with AIExpertise in model prompting, context engineering, and orchestration patterns for autonomous workflowsStrong AI/ML engineering experience with foundation models and frameworks (e.g., LangChain/LangGraph)Experience with hyperscale cloud platforms (AWS/Azure/GCP) and frontier model APIs (Anthropic, OpenAI)Fluency with AI-assisted development tools and cost/performance optimization techniquesStrong API design, microservices, SDLC, and CI/CD skillsIndependent, innovative, and able to mentor other engineers and set technical directionStrong collaboration and communication across technical and non-technical stakeholdersCross-functional collaborationStrong communicationIndependence and initiativeAI/ML engineeringFrontier models (Claude, OpenAI, Qwen)LangChain or LangGraph