Lead AI​/Machine Learning Engineer

The Disney Decision Science + Integration (DDSI) is a consulting team that supports clients across The Walt Disney Company, including Disney Experiences, Disney Entertainment, ESPN, and Corporate Finance. DDSI partners with Marketing, Finance, Business Development, Research, and Operations to develop, analyze, and execute strategies that improve value for Guests, Cast Members, and Shareholders. The team uses technology, data analytics, optimization, and statistical/econometric modeling to shape business decisions and drive business value.

This position, based in an office setting, seeks a results‑oriented, hands‑on AI/ML Engineer passionate about Generative AI and LLMs. The engineer will design, build, and deploy AI initiatives that drive business value, overseeing projects from concept to delivery, writing production‑grade code, and collaborating with cross‑functional teams.

• Architect, design, and develop AI applications, integrating with AWS Bedrock, Google Vertex AI, Microsoft Azure, and other LLM suites.
• Build and deploy complex, scalable AI solutions, including multi‑step agentic workflows and multi‑agent systems.
• Orchestrate AI agents capable of complex reasoning, planning, and dynamic tool use to solve business problems.
• Design and implement effective prompts, configure LLM settings, and optimize output through prompt crafting, context engineering, RAG, fine‑tuning, and other techniques.
• Develop and manage robust evaluation strategies and frameworks for LLMs and agentic systems, assessing model quality, task completion reliability, safety, and effectiveness.
• Act as a technical expert, guiding design decisions and ensuring adherence to best practices in AI development, LLMOps, testing, and deployment.
• Collaborate with product managers, data scientists, client teams, vendors, and other partners to define requirements, adapt plans, and achieve successful outcomes.
• Identify and mitigate technical risks and roadblocks impeding project delivery.
• Represent the technical aspects of initiatives with senior leaders and partners.
• Contribute hands‑on to development and troubleshooting, particularly on challenging technical problems.
• Lead research and development efforts into emerging tools and technologies, focusing on Generative AI, LLMs, and related areas.
• May manage direct reports and/or lead junior team members, including professional staff in a matrixed organization.

• 7+ years of experience designing, building, and deploying AI/ML solutions, with 1–2 years of hands‑on experience with GenAI technologies.
• Experience with Retrieval‑Augmented Generation (RAG) architectures.
• Familiarity with vector databases such as Milvus, Pinecone, and Chroma
  
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• Expertise in AI application and agentic frameworks (e.g., Lang Chain, Lang Graph, Google ADK, Strands Agents, OpenAI Agents SDK, CrewAI, Llama Index).
• Experience with cloud platforms such as Google Vertex AI, AWS Bedrock, or Microsoft Azure.
• Strong understanding of data preprocessing for LLMs, including tokenization, embedding, and feature engineering.
• Proficiency in prompt and context engineering techniques.
• Strong proficiency in core programming languages used in AI/ML (e.g., Python).
• Deep understanding of AI agent architectures, including planning, memory, and tool integration (e.g., ReAct).
• Solid experience applying MLOps principles and tools for model deployment, monitoring, and lifecycle management.
• Experience with code generation assistance tools (e.g., Git Hub Copilot, Amazon Q Developer, Cursor).
• Experience with traditional ML algorithms and statistical modeling techniques.
• Excellent analytical and problem‑solving skills.
• Strong communication and collaboration skills, enabling effective articulation of technical concepts across teams.
• Demonstrated ability to partner with diverse clients and partners of varying job levels.
• Experience working in a matrixed organization where influencing others is critical to success.

• Certifications in AI, machine learning, or relevant cloud platforms.
• Experience designing and orchestrating multi‑agent systems.
• Competency in data science topics including statistics, optimization,…