engineer principal - AI Experiences, Green Dot Assist

Now Brewing – Engineer (Principal) AI Experiences, Green Dot Assist! #tobeapartner

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.

As a principal engineer, AI Experiences, Green Dot Assist, you will...
 

Define the Future of Enterprise AI Experiences

• 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.

Lead Enterprise Application Platform Strategy

• 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.

Create a Unified User Experience Architecture

• 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.

Drive AI and Intelligent Automation Adoption

• 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 technologies.

Advance Context & Knowledge Engineering

• Support and champion the development of semantic models, metadata strategies, business ontologies, and knowledge frameworks that improve AI effectiveness.
• Enable systems to understand relationships between data, processes, users, and business concepts.
• Drive contextualization strategies that improve discoverability, reuse, and decision quality.
• Establish foundations for enterprise-scale intelligent systems.

Governance, Security & Platform Standards

• Support leaders in the development of scalable access control and authorization patterns for business-facing applications and AI experiences.
• Create reference architectures and engineering standards that support secure, compliant, and maintainable systems.
• Ensure innovation can occur without creating fragmentation, duplication, or operational risk.

Technical Leadership

• Serve as a recognized technical authority across multiple organizations.
• Influence architecture strategy at senior leadership levels.
• Mentor engineers, architects, and technical leaders.
• Lead architecture reviews, technology evaluations, and standards development.
• Drive alignment across engineering, product, security, user experience, and business stakeholders. 

We’d love to hear from people with...

Required Qualifications

• 10+ years of experience in software engineering, data engineering, platform engineering, enterprise architecture, or related disciplines.
• Demonstrated experience designing and scaling enterprise platforms and distributed systems.
• Deep understanding of cloud-native architectures, APIs, application frameworks, and modern software delivery practices.
• Experience designing systems that balance usability, governance, security, and scalability.
• Strong background in analytics, AI, data-powered applications, or intelligent systems.
• Proven ability to influence technical direction across organizational boundaries.
• Exceptional communication and stakeholder management skills.
• Experience with generative AI, conversational interfaces, intelligent agents, or recommendation systems.

Preferred Qualifications

• Knowledge of metadata management, semantic technologies, knowledge graphs, and ontology-driven architectures.
• Experience designing highly governed enterprise applications and platforms.
• Familiarity with enterprise-scale analytics and decision-support environments.
• Experience integrating operational workflows with analytical and AI-driven capabilities.

What Success Looks Like:
Within the first 12–18 months, this leader will:

• Define a clear enterprise strategy for Multi-Agent AI-enabled business experiences.
• Establish architectural patterns for intelligent applications and decision-support systems.
• Create a scalable framework for application development and governance.
• Reduce fragmentation across enterprise applications, reporting tools, and analytical experiences.
• Enable teams to innovate rapidly while maintaining consistency, security, and operational excellence.
• Improve access to trusted information and accelerate decision making across the organization.
• Lay the foundation for a future where intelligent systems proactively assist users, recommend actions, and automate routine decision-making processes.