Director AI/ML Platforms and Shared Services

Hyatt Hotels Corporation; Chicago (IL); Presencial; USD 176 000 - 235 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Free hotel stays

Flexible work schedule

Headspace subscription

Wellbeing programs

Family assistance policy

Resumo da oferta

Hyatt Hotels Corporation seeks a Director to lead AI platforms and shared services within the Data and Analytics group. You will own architecture, runtimes, and integration for enterprise AI agents, collaborating with ML teams and platform groups.

You will drive end-to-end delivery, mentor engineers, and influence production readiness on AWS/GCP with a strong emphasis on reliability, security, and cost efficiency.

Qualificações

• 5+ years leading engineering teams with hands-on architecture involvement.
• Experience designing and operating end-to-end platforms used by multiple teams.
• Building production AI systems with evaluation, deployment, observability, and integration.
• Experience with AWS and/or GCP in production environments.

Responsabilidades

• Define and execute the strategy and roadmap for AI platforms and shared services.
• Lead architecture, API design, and data flows for scalable agent runtimes.
• Mentor teams, review code, and ensure production reliability and cost control.
• Partner with Platform/Infrastructure teams to meet enterprise needs.

Conhecimentos

Leadership

Python

Distributed systems

Architecture

Formação académica

Master's degree

Equivalent practical experience

Ferramentas

Docker

Kubernetes

Terraform / IaC

CI/CD

Descrição da oferta de emprego

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.

Who We Are

At Hyatt, we believe in the power of belonging and creating a culture of care, where our colleagues become family. Since 1957, our colleagues and our guests have been at the heart of our business and helped Hyatt become one of the best and fastest-growing hospitality brands in the world. Our transformative growth and the addition of new hotels, brands, and business lines can open the door for exciting career and growth opportunities for our colleagues.

As we continue to grow, we never lose sight of what's most important: People. We turn trips into journeys, encounters into experiences, and jobs into careers.

Why Now?

This is an exciting time to be at Hyatt. We are growing rapidly and are looking for passionate changemakers to be a part of our journey. The hospitality industry is resilient and continues to offer dynamic opportunities for upward mobility, and Hyatt is no exception.

How We Care for Our People

What sets us apart is our purpose-to care for people so they can be their best. Every business decision is made through the lens of our purpose, and it informs how we have and will continue to support each other as members of the Hyatt family. Our care for our colleagues is the key to our success. We're proud to have earned a place on Fortune's prestigious 100 Best Companies to Work For list since 2013. This recognition is a testament to the tremendous way our Hyatt family continues to come together to care for one another, our commitment to a culture of inclusivity, empathy, and respect, and making sure everyone feels like they belong.

• Annual allotment of free hotel stays at Hyatt hotels globally
• Flexible work schedule
• Work-life benefits including wellbeing initiatives such as a complimentary Headspace subscription, and a discount at the on-site fitness center
• A global family assistance policy with paid time off following the birth or adoption of a child as well as financial assistance for adoption
• Paid Time Off, Medical, Dental, Vision, 401K with company match

Who You Are

As our ideal candidate, you understand the power and purpose of our culture of care, and embody our core values of Empathy, Inclusion, Integrity, Experimentation, Respect, and Wellbeing. You enjoy working with others, are results-driven, and are looking for a variety of opportunities to develop personally and professionally.

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.

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.