Principal Data Architect

We Power the Magic!" That's our motto at Disney Experiences (DX) Tech & Digital. Our team creates world-class immersive digital experiences for the Company's premier vacation brands. We deliver experiences to consumers through our Disney's Parks & Resorts worldwide, Disney Cruise Lines, and Disney Vacation Club. We are responsible for the end-to-end digital and physical Guest experience for all technology & digitally led initiatives across the Attractions & Entertainment, Food & Beverage, Resorts & Transportation and Merchandise lines of business, as well as other initiatives such as Hey, Disney!

This role sits in the JedAI Platform team as a Principal Data Architect and will report to the Sr. Manager.

In this role, you will be positioned as an expert in Generative AI across Disney Experiences specifically driving advanced data architectures. This role will be responsible for delivery of high-quality AI solutions within highly visible strategic projects and requires active collaboration with cross-functional teams.

Responsibilities:

• Assess both internal and external business and product requirements providing sophisticated guidance and innovative solutions for generative AI applications and storage for evolving needs and industry standards.
• Design, develop and lead the strategic implementation of advanced, scalable, high-performing generative AI architectures, including data pipelines, model training frameworks, and deployment strategies.
• Leverage profound technical expertise, specifically integrating sophisticated automation and advanced automation methodologies like big data, AI and machine learning to ensure the quality, consistency, and security of data used to train and run generative AI models.
• Stay at the forefront of generative AI research and development, identifying new techniques and tools to improve model performance and efficiency.
• Establish and uphold exacting design and governance frameworks for the ethical and responsible use of generative AI technologies.
• Engage in estimation planning, providing technical recommendations and solutions during planning activities and contribute to proposal development.
• Communicate complex AI concepts clearly and concisely to both technical and non-technical audiences.
• Monitor, evaluate, and optimize generative AI solutions to ensure they meet business objectives.
• Document and share knowledge to foster a culture of continuous learning and improvement within the team.
• Operationalize best practices around different vector search technologies search as neo4j, Vertex Search, Elastic Search, Weaviate etc.
• Evaluate NLP outcomes with data science metrics and implement outcome monitoring and feedback loop into the data pipeline.

Qualifications:

• 10+ years related work experience. Proven experience in designing and building scalable data architectures for machine learning / AI applications.
• In-depth knowledge of generative AI models (e.g., GANs, VAEs) and their applications.
• Experience with RAG, vector stores, sematic search, chunking strategies, embedding models, and large data handling for LLMs.
• Strong understanding of data engineering principles and best practices (e.g., data cleansing, transformation, feature engineering).
• Experience working with cloud platforms (e.g., AWS, Azure, GCP) is a plus.
• Excellent communication, collaboration, and problem-solving skills.
• Ability to translate business needs into technical solutions.
• Passion for innovation and a commitment to ethical AI development.
• Experience building LLMs pipeline using framework like LangChain, LlamaIndex, Semantic Kernel, OpenAI functions.
• Familiar with different LLM parameters like temperate, top-k, and repeat penalty, and different LLM outcome evaluation data science metrics and methodologies.

Required Education: Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.

Preferred Education: Master's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.