Summary:The Opportunity Hyatt Hotels Corporation seeks an enthusiastic Director to join our Data and Analytics department. In this role, you will be collaborating closely with the broader Machine Learning and AI team, where you'll be instrumental in continuing to make Hyatt a leading hospitality company. You will be part of a team that is passionate about our purpose, committed to nurturing curiosity and new skills, and building connections across the organization with colleagues, customers, and guests.
The Role The Director of AI Platforms and Shared Services leads the strategy, system architecture, and hands-on delivery of internal products that enable AI product engineering teams to build and operate AI applications and agents for business stakeholders. This leader treats internal engineering teams as customers, translating shared needs into reliable, reusable, self-service capabilities that simplify development and accelerate the path to production.
The role owns the technical vision and delivery roadmap for agent platforms, including agent runtimes and orchestration, tool and enterprise system integration, memory and context management, and agent evaluation and observability. Supporting shared services include inference, model deployment pipelines, feature stores, and enterprise embedding services backed by vector databases. Together, these capabilities support the lifecycle of agents and models, including versioning, validation, deployment, monitoring, and model registration and explainability. System design is central to the position: defining service boundaries, APIs, data flows, permissions, and deployment patterns while making practical tradeoffs across scalability, latency, reliability, security, and cost. The director brings experience owning and evolving end-to-end systems and uses that perspective to address product team needs while partnering closely with Platform and Infrastructure teams to meet enterprise requirements.
This is a player-coach role that combines team leadership with direct technical contribution. The director leads from the front, remaining actively involved in architecture, prototyping, Python development, design and code reviews, and solving difficult production problems across AWS and GCP. They build and develop a strong engineering team, establish sound engineering practices, and stay accountable for shared services from initial design through production operations and ongoing evolution. Success is measured by the usefulness and reliability of the internal products, reduced duplication across teams, and how easily engineers can move AI applications, agents, and models from experimentation into production.
Qualifications: Experience Required: - 10+ years of software engineering experience spanning AI engineering, machine learning engineering, or cloud platform engineering, including significant ownership of production systems.
- 3+ years leading engineering teams, with continued hands-on involvement in architecture, development, and technical problem solving.
- Demonstrated experience designing, delivering, operating, and evolving end-to-end platforms or shared services used by multiple engineering teams.
- Experience building production agent or AI systems, including evaluation, deployment, observability, and integration with enterprise systems.
• Experience partnering with Platform, Infrastructure, Security, and product engineering teams to balance product needs with enterprise requirements.
• Master's degree in Computer Science, Engineering, Mathematics, Physics, or a related technical discipline, or equivalent practical experience.
• Strong system design skills, including distributed systems, service boundaries, application programming interfaces, design patterns, and tradeoffs across reliability, performance, security, and cost.
• Strong Python development skills and experience building reusable libraries, services, and developer tools.
• Experience with agent runtimes and orchestration, tool integration, memory and context management, retrieval, evaluation, and observability.
• Experience with shared AI infrastructure, including inference services, embedding services, vector databases, and model deployment pipelines.
• Understanding of AI and machine learning fundamentals and lifecycle capabilities, including registration, versioning, validation, deployment, monitoring, and explainability.
• Experience with AWS and GCP, including deep production expertise in at least one.
• Experience with Docker, container orchestration, infrastructure as code, automated testing, and continuous integration and continuous delivery.
• Experience with agent interoperability protocols, feature stores, experimentation platforms, recommender systems, or forecasting systems preferred.
The position responsibilities outlined above are in no way to be construed as all-encompassing. Other duties, responsibilities, and qualifications may be required and/or assigned as necessary.
We welcome you: Research shows that individuals tend to apply to jobs only if they meet all the listed job qualifications. Unsure if you check every box, but feeling inspired to enhance your career? Apply. We'd love to consider your unique experiences and how you could make Hyatt even better.
The salary range for this position is $176,300 - $235,000
The final pay rate/salary offered to the successful candidate will depend on experience, skill level and other qualifications for the role, as well as the location of the performance of work. Pay for the successful candidate will meet local requirements, including the local minimum wage rate.
We value our relationships with recruitment partners and require that agencies contact us first before submitting any candidates. Hyatt will not be responsible for any fees and obligations associated with unsolicited submissions unless a formal agreement is in place.
