Americas BPR-Engineering Project Manager

Austin, Texas, United States Operations and Supply Chain

Apple is where extraordinary people do their best work. If making a real impact excites you, a career here might be your dream — just be prepared to dream big. Apple's growing supply chain complexity demands innovative approaches to automation and operational excellence. You'll join the Business Process Reengineering team to scale Apple Operations in the supply chain space. You're passionate about understanding the big picture while diving into technical details, adapting your communication style to bridge business perspectives, engineering pipelines, and supply chain optimization.

You thrive exercising interpersonal, organizational, technical, and analytical skills in a fast-paced environment. If this sounds like you, we'd love to talk.

An EPM in this role drives end-to-end delivery of complex, cross-functional AI/ML and supply chain programs by owning technical solution roadmaps, milestones, and execution across engineering, product, and business teams to ensure on-time, high-quality launches. They dive deep into technical designs, data, and system architecture, infrastructure and Cloud based solutions alongside engineers and data scientists, leveraging their knowledge of software engineering, GenAI, MLOps, and agentic AI to unblock issues, manage risks, and make informed prioritization trade-offs.

They align diverse stakeholders through clear communication, data-driven decision-making, and structured executive narratives continuously improving processes to increase velocity and translate technical complexity into measurable business impact.

• Masters degree in Computer Science, Engineering, Analytics, or equivalent technical field and 8+ years of technical/engineering program management experience OR Bachelor’s in Computer Science, Engineering, Analytics, or equivalent technical field with 10+ years experience
• Previous experience with software engineering, GenAI, Machine Learning, AI, and supply chain/operations domains
• Dive deep into data, technical designs, and root-cause analysis to resolve complex challenges with high analytical rigor
• Proficiency with data acquisition tools advanced SQL, Python, data visualization, and analytics platforms
• Familiarity with agentic AI frameworks, tool-use patterns (e.g., MCP servers, function calling, skills), and the ability to evaluate how autonomous agents and multi agent network can be applied to program and operational workflows
• Knowledge of large language models (LLMs) and prompt engineering techniques — sufficient to partner effectively with software engineers and data scientists on GenAI-powered solutions
• Understanding of MLOps best practices including model deployment pipelines, CI/CD for ML workflows, model versioning, and drift monitoring to support production AI/ML systems
• Experience managing feature roadmaps across interconnected systems, with the ability to stitch together supply chain concepts (e.g., fulfillment, logistics, demand planning) into cohesive program strategies
• Familiarity with software engineering best practices including testing frameworks, code quality standards, secure development practices, system architecture, strong understanding of APIs, data architecture, and system integration enabling effective partnership with software engineering teams on technical deliverables

• Operate effectively in ambiguous environments, demonstrating strong ownership, bias for action, sound judgment, and a commitment to delivering results with experience working in Agile/Scrum environments
• Own end-to-end delivery of complex, cross-functional technical programs from concept through launch and post-launch operational excellence, ensuring alignment with long-term business and customer impact
  
  Define program vision, multi-quarter roadmaps, clear milestones, and measurable success criteria; drive execution across engineering, product, and business stakeholders
• Partner with engineering leaders to review and influence system architecture, scalability, reliability, and long-term maintainability of solutions
• Drive prioritization decisions in partnership with AIML and engineering teams, balancing customer impact, cost, resourcing, timeline, and technical risk
• High intellectual curiosity to learn and understand business needs, with the ability to provide in-depth evaluations of complex engineering and analytic issues
• Proactively identify cross-team dependencies, risks, and trade-offs; implement mitigation plans to ensure predictable, high-quality delivery
• Establish mechanisms to monitor program health, including business-critical metrics, operational dashboards, and recurring inspection reviews
• Earn trust and alignment across multiple teams by influencing without authority and facilitating clear, data-driven decision-making
• Continuously improve development and operational processes by inventing and simplifying workflows to increase velocity and reduce defects
• Communicate…