Senior Software Engineer - AI Core Engineering

Senior AI Engineer

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.

We're hiring a Senior AI Engineer to build the AI core capabilities and tooling that accelerate teams across Ad Technology. You will create shared agents, initializers, registries, and reusable services and web applications that make it fast, safe, and cost-effective for engineering squads to adopt AI.

Your work will emphasize common design principles, guardrails, governance, observability, and evaluation, so teams can deliver high-quality AI solutions quickly—without reinventing the basics.

This role blends backend engineering, LLM orchestration, and developer enablement. You'll design APIs, SDKs, reusable agents, and web-based solutions that standardize adoption, define patterns for multi-turn interactions, and provide evaluation/traceability so teams can confidently scale AI across Disney Ad Tech.

Responsibilities and Duties of the Role:

• Define and implement shared design patterns for agents and services, including context management, retrieval, safety, and evaluation.
• Establish reusable blueprints that standardize how AI solutions are built across Ad Tech.
• Build production-ready agents, initializers, and libraries for common use cases (summarization, troubleshooting, semantic extraction).
• Develop high-quality APIs and SDKs that simplify adoption of AI capabilities by other engineering teams.
• Deliver core services for retrieval, memory, and orchestration, integrated with enterprise and consumer facing systems.
• Create internal webapps and dashboards that expose AI capabilities, evaluation metrics, and adoption accelerators.
• Embed guardrails, compliance checks, and prompt safety into all shared components.
• Implement model evaluation and observability frameworks for quality, reliability, and cost monitoring at scale.

Basic Qualifications:

• 5+ years of backend or applied AI/ML engineering with a track record of building production-grade systems.
• Proficiency in Python (libraries, testing, packaging) and building scalable APIs or SDKs.
• Hands-on experience with LLM APIs (e.g., OpenAI, Anthropic, Claude) and frameworks such as LangChain or LangGraph.
• Experience integrating with enterprise AI services such as AWS Bedrock or Azure AI Foundry, including model invocation, routing, and governance integration.
• Experience developing reusable agents, libraries, or internal tooling adopted by multiple teams.
• Knowledge of guardrails and evaluation techniques for LLMs, including prompt safety, output validation, and quality regression testing.
• Strong collaboration and communication skills; able to work across infra, data, security, and product teams.

Preferred Qualifications:

• Experience building AI enablement tooling (registries, agent initializers, internal frameworks) for enterprise use.
• Familiarity with observability for AI systems: tracing, latency and cost dashboards, drift detection.
• Knowledge of AI gateway patterns (e.g., routing, usage throttling, model fallback, quota enforcement).
• Exposure to multi-agent orchestration, simulation frameworks, or synthetic data for testing/eval.
• Understanding of enterprise governance: security, compliance, audit, and policy enforcement in AI systems.
• Previous experience in a developer enablement role (platform engineering, frameworks, SDKs) where reusable components accelerated adoption across large organizations.

Required Education:

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