engineering manager, Data and AI Platform engineering (Seattle, WA) at Starbucks

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

09 Mar, 26

Salary

0.0

Posted On

09 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Machine Learning, AI Platforms, Cloud Infrastructure, Distributed Systems, Containerization, Orchestration, CI/CD Technologies, Agile, SCRUM, Scripting Languages, Monitoring, Logging, Data Governance, Technical Leadership, Team Management

Industry

Retail

Description

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. 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. Oversee training and development of partners directly and indirectly and make effective staffing decisions. 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 (e.g. LangChain, LangGraph, Semantic Kernel, TensorFlow, PyTorch), and APIs Proficiency with at least 1 scripting language (e.g. Python, Powershell, Go) Proficiency in RAG pipelines, multi-agent orchestration, and tool use is critical. Skilled in Agile/SCRUM project and release management methodologies. Ability to identify, analyze and resolve complex technical issues, ensuring optimal performance, scalability and user experience. Strong communication and collaboration skills with cross-functional partners, including those with and without technical backgrounds. Demonstrated willingness to learn continuously, adopt new technologies and approaches, and share knowledge within the technical community. Growth-minded, solution-oriented approach with a proven track record of driving projects from concept to impact. Experience in managing geographically distributed teams. 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. Implement foundational data infrastructure and tools required for large scale data processing including orchestration, storage, compute, and access management. 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. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, or protected veteran status, or any other characteristic protected by law. Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances.

Responsibilities

Develop technology vision and roadmap for data, ML, and agentic AI platform while leading a team of engineers. Collaborate with various teams to deliver platform solutions and advance technical strategy.