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Principal engineer-AI Sourcing & Procurement; Nashville, TN

Job in Nashville, Davidson County, Tennessee, 37247, USA
Listing for: Starbucks
Full Time position
Listed on 2026-06-18
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 150000 - 200000 USD Yearly USD 150000.00 200000.00 YEAR
Job Description & How to Apply Below
Position: principal engineer-AI Sourcing & Procurement(Nashville, TN)

Now Brewing – Engineering Principal, AI Sourcing & Procurement Platforms (Nashville, TN)

Location:

Nashville, TN (Onsite – four days per week)

From the beginning, Starbucks set out to be a different kind of company—one that not only celebrated coffee and its rich tradition, but also built meaningful connections. We are known for developing extraordinary leaders who are guided by service to others and driven to make an impact at global scale.

We are seeking a hands-on Engineering leader to head the development of AI-powered sourcing and procurement platforms, modernizing how Starbucks plans, sources, negotiates, and executes across a complex global supply chain. This leader will build and scale secure, reliable, and high-velocity AI systems that directly impact cost, availability, and operational resilience.

This role is based in Nashville and sits at the intersection of AI engineering, enterprise platforms, and real-world business execution, with an expectation of rapid iteration, strong technical rigor, and close partnership with procurement, supply chain, and business teams.

Technical Strategy & Thought Leadership
  • Define and drive the technology vision and roadmap for AI-enabled sourcing and procurement platforms, balancing speed, scalability, security, and reliability.
  • Partner closely with procurement, supply chain, finance, product, and data science teams to translate business needs into AI-driven capabilities (e.g., sourcing optimization, supplier intelligence, contract insights).
  • Own architectural decisions for LLM-powered and agentic systems, ensuring platforms evolve safely and predictably as models, tools, and use cases change.
  • Operate effectively in a dynamic, fast-moving environment, with wicked-fast deployment cycles and a bias toward responsible delivery over perfection.
Team Leadership And Management
  • Lead and mentor a team of platform, infrastructure, and AI engineers, fostering a culture of ownership, learning, and execution.
  • Set clear technical standards and expectations while empowering engineers to move quickly and safely.
  • Coach partners through ambiguity, trade-offs, and real-world constraints common in applied enterprise AI.
  • Like all good AI roles, this one is a hands on and requires servant leadership in demonstrating what good looks like.
Engineering Management Infrastructure & Operational Excellence
  • Enable high developer productivity through CI/CD, infrastructure-as-code, Kubernetes, and automated testing, with a strong emphasis on deployment speed and reliability.
  • Establish and use operational metrics (DORA metrics, SLOs, SLIs, error budgets) to balance innovation with stability.
  • Implement best-in-class monitoring, logging, and alerting to ensure platform health and rapid incident response.
  • Lead thoughtful decisions around model tradeoffs, token usage, cost optimization, and performance in production AI systems.
Applied AI:
Rigor, Safety & Trust
  • Ensure back testing, AI evaluations, and performance benchmarking are integral to model and agent development—not optional afterthoughts.
  • Embed AI security, data protection, and access controls by design, partnering closely with Security and Architecture teams.
  • Drive disciplined practices around prompt management, model versioning, regression testing, and controlled rollout of AI capabilities.
  • Ensure AI systems are explainable, auditable, and appropriate for enterprise sourcing and procurement use cases.
Technical Environment & Tooling
  • Hands-on familiarity with modern AI development tools, including Git Hub Copilot, Cursor, and similar AI-assisted engineering tools, and an expectation to model their effective use.
  • Build and operate systems leveraging LLMs, agentic orchestration, and intelligent workflows aligned to real business outcomes.
  • Collaborate across data platforms and enterprise systems supporting procurement and supply chain operations.
Basic Qualifications
  • Bachelor’s degree in computer science or information systems or equivalent experience.
  • Minimum 10 years of technology related work experience
  • Minimum 2 years leveraging LLMs in development
  • Must love to code and work through engineering challenges using GenAI
Experience Required
  • 8+ years of…
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