Engineering manager, Data and AI Platform engineering; Seattle, WA

Engineering Manager, Data and AI Platform Engineering (Seattle, WA)

Base pay range: $/yr – $/yr

Now Brewing – Engineering Manager, Data and AI Platform engineering

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.

We are seeking a hands‑on Engineering Manager to lead the development and evolution of our AI and Data Platforms within the Data & Analytics organization. These platforms will serve as the foundation for multiple data, data science and AI teams to build data‑driven and AI‑powered Agentic products. You will play a critical role in shaping the technology, architecture and frameworks advancing build of agentic capabilities across the enterprise ensuring scalability, security, and reliability of the platform.

• Technical Strategy & Thought Leadership:
  Develop technology vision and roadmap for data, ML and agentic AI platform focusing on security, scalability and reliability. Partner with data science, data engineering, governance and product teams to understand product strategy, and deliver platform and developer solutions. Lead discussions with business stakeholders and craft solutions/improvements to advance both technical strategy and business capabilities.
• Team Leadership and Management:
  Lead and mentor a team of infrastructure, platform and AI engineers, fostering a culture of innovation and excellence. Challenges and inspires team members to achieve business results. Provides coaching, direction and leadership support to team members to achieve business and customer results. Oversees training and development of partners directly and indirectly and makes effective staffing decisions.
• Engineering Management – Infrastructure & Operational Excellence:
  Oversee the design, implementation, and management of core infrastructure components (cloud, networking, storage, compute) to ensure they are scalable, reliable, secure, and cost‑effective for data, ML & AI applications. Empower developers by simplifying development process including continuous integration/continuous delivery (CI/CD) pipelines, infrastructure as code (IaC), Kubernetes and automated testing. Establish and use key metrics (e.g., DORA metrics, SLOs, SLIs, error budgets) to monitor system health and drive continuous improvement in operational practices and incident management.
  
  Implement and manage monitoring, logging, and alerting to ensure the platform’s health and performance.
• Data & AI (gen AI included) Platform:
  Implement foundational data infrastructure and tools required for large scale data processing including orchestration, storage, compute, and access management. Partner with Security and Architecture teams to embed security and architecture best practices and guardrails into the tools and features by design. Implement, build and manage enterprise metadata catalog & governance systems; enable advanced technical capabilities for data classification, tagging etc.
  
  to enable data for AI and agentic consumption. Drive the design and development of agentic frameworks, orchestration layers, and AI‑driven product capabilities, leveraging LLMs, intelligent automation, and adaptive workflows, including prompt management, performance benchmarking etc. Define strategy, infrastructure and controls for…

• Bachelor’s degree in computer science or information systems or equivalent experience.
• Minimum 10 years of technology related work experience.
• Minimum 3 years managing a team of 5+ engineers.

• 8+ years of building scalable services on top of public cloud infrastructure, preferably Azure.
• 8+ years’ experience designing, building and operating large‑scale distributed systems and infrastructure.
• 5+ years’ experience with data and AI platforms (e.g., Databricks, Azure, Snowflake).
• Deep knowledge of containerization & orchestration (Kubernetes, Docker), IaC and CI/CD technologies.
• Experience working with AI and Machine Learning frameworks…