senior lead, DevEx GenAI Enablement; Seattle WA

Starbucks Coffee Company•Seattle, WA

2d•Hybrid

About The Position

The Senior Software Engineer - AI Automation & Developer Productivity is a hands-on technical role within our Developer Productivity and Automation organization. This role focuses on designing, building, and operating shared cloud-native platforms and AI-powered automation that enable engineering teams to build, test, and release software more effectively at scale. This engineer brings a platform mindset, thrives in ambiguous problem spaces, enjoys getting hands-on with code, and partners closely with product, platform, DevOps, and SRE teams to deliver production-ready capabilities used by many teams across the organization.

Requirements

8-10 years of professional industry experience with software development
2 years of leading teams of four or more software developers
Bachelor’s degree in Computer Science or related field engineer lead
7+ years of experience in system administration, network administration, and systems engineering
7+ years of experience in one or more of the following languages: C, C++, Java, Python, Go, Perl and/or Ruby.
5+ years Experience with large-scale distributed systems and client-server architectures
Demonstrated ability to debug and optimize code, and automate routine tasks.
Interest in designing, analyzing and troubleshooting large-scale distributed systems.
Proven ability to translate insights into business recommendations
Deep Knowledge in application development and supporting a development environment
Experience with Cloud Computing platforms (e.g. Amazon AWS, Microsoft Azure, Google App Engine)
Demonstrated experience implementing and managing high capacity, redundant, and mission critical environments

Nice To Haves

Experience applying Generative AI or AI/ML techniques to software development, quality engineering, or automation workflows.
Experience building agentic or GenAI-powered systems using frameworks and platforms such as LangChain, AWS Bedrock, or similar orchestration and model hosting technologies.
Familiarity with agentic AI concepts including LLM orchestration, autonomous agents, retrieval-augmented generation (RAG), prompt engineering, and vector databases.
Experience designing enablement platforms, SDKs, or reusable services that allow other teams to build and extend AI-driven or automation workflows independently.
Experience defining guardrails, abstractions, and operational standards that enable teams to safely adopt AI and agent-based systems at scale.
Experience working with open-source LLMs and AI frameworks.
Hands-on experience with data platforms and streaming technologies such as Kafka, Spark, Hadoop, or Databricks.
Knowledge of MLOps practices including model deployment, monitoring, governance, and lifecycle management.
Experience building internal developer platforms, tooling, or productivity solutions.
Ability to mentor other engineers through technical leadership and example, without direct people management responsibility.

Responsibilities

Designs, builds, and operates AI-powered automation and agent-based systems across multiple phases of the software development lifecycle (SDLC).
Designs and builds shared cloud-native platforms, services, and frameworks that enable other engineering teams to build, deploy, and operate AI agents and automation safely and efficiently.
Provides paved-road infrastructure, APIs, templates, and reference implementations that accelerate adoption of agentic and GenAI capabilities across multiple teams.
Implements agentic workflows to analyze requirements, generate test scenarios, identify risks, and surface quality gaps early in the development cycle.
Develops AI-driven solutions for automated testing, performance testing, quality validation, and A/B experimentation.
Integrates AI-driven quality checks, code analysis, and validation into CI/CD pipelines in partnership with DevOps and SRE teams.
Builds and maintains scalable automation frameworks for data processing, model execution, validation, and deployment.
Writes clean, efficient, and well-structured software in an iterative, continuous delivery environment.
Participates actively in design reviews, code reviews, and incident retrospectives to uphold engineering excellence.
Evaluates emerging AI, GenAI, and automation tools through prototypes and proofs of concept, recommending scalable adoption strategies.
Contributes to and promotes strong software engineering practices including testing, observability, documentation, and operational readiness.
Communicates complex technical concepts clearly to both technical and non-technical stakeholders.

Benefits

medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits.
short-term and long-term disability
paid parental leave
family expansion reimbursement
paid vacation from date of hire
sick time (accrued at 1 hour for every 25 hours worked)
eight paid holidays
two personal days per year.
participation in a 401(k) retirement plan with employer match
discounted company stock program (S.I.P.)
Starbucks equity program (Bean Stock)
incentivized emergency savings
financial well-being tools.
100% upfront tuition coverage for a first-time bachelor’s degree through Arizona State University’s online program via the Starbucks College Achievement Plan
student loan management resources
access to other educational opportunities.
backup care
DACA reimbursement.