Engineer principal - AI , Green Dot Assist

From the beginning, Starbucks set out to be a different kind of company. One that not only celebrated coffee and the rich tradition, but that also brought a feeling of connection. We are known for developing extraordinary leaders who share this passion and are guided by their service to others.

As a Principal Engineer (AI) , you’ll play a critical role in delivering high-quality, reliable, and secure Generative AI technology that enables coffee house partners and leaders to operate effectively, deliver results with quality and be more customer focused. This advanced role focuses on owning complex engineering capabilities end-to-end—partnering across business and technology teams to bring in AI capabilities where it matters most in a cost effective, performant way with reliability, scalability, and operational excellence at the core.

This role supports the development of artificial intelligence, multi-agent orchestration strategies, application architecture, seamless integrations with user experience, and building right security, legal and governance controls with Responsible AI principles. The successful candidate will be responsible for shaping how a multi-agent orchestration engine and deliver unified experiences to coffee house partners and leaders to effectively operate and bring needed customer focus to coffeehouse operations.

The ideal candidate will support the development of the architecture, standards, and AI engineering best practices that help scale and mature a multi-agent eco‑system in a governed , scalable, and secure user experiences. This includes defining how conversational interfaces, intelligent applications, workflow systems, analytical tools, and decision‑support technologies come together as a cohesive ecosystem.

A key aspect of the role is helping the organization evolve from fragmented reporting and application experiences toward unified, AI‑enabled platforms that deliver context‑aware insights, recommendations, automation, and action‑oriented decision support.

• Establish the long‑term vision for how users discover, access, and interact with enterprise knowledge, analytics, and intelligent systems.
• Define architectural patterns for conversational interfaces, AI assistants, recommendation engines, and agent‑based solutions.
• Create a cohesive strategy that connects data, analytics, workflows, and AI into seamless business experiences.
• Guide the evolution toward proactive, context‑aware decision support and automation.

• Define the architecture of modern business applications built on governed enterprise data.
• Establish standards for application hosting, user experience, integration, deployment, and lifecycle management.
• Create scalable frameworks that allow teams to rapidly develop applications while maintaining consistency, governance, and security.
• Drive simplification and rationalization across overlapping application and reporting technologies.

• Support leaders to establish principles that provide users with a consistent way to discover and access business capabilities.
• Enable a marketplace‑style experience that balances self‑service innovation with governance and operational control.
• Ensure experiences remain intuitive regardless of the underlying technology stack.

• Partner with business and technology teams to identify opportunities where AI can accelerate decision making and reduce manual effort.
• Define reusable patterns for intelligent workflows and automated actions.
• Establish standards for integrating AI capabilities into operational and analytical experiences.
• Promote responsible and governed adoption of emerging AI…