About The Position

Imagine what you could do here. At Apple, new ideas quickly become exceptional products, services, and experiences. Bring passion and dedication to your work and there’s no telling what you can accomplish. Apple teams don’t just build products — they create the kind of wonder that reshapes entire industries. The diversity of our people and their ideas fuels innovation across everything we do, from world-class technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. The IS&T ETS Insight organization is seeking a dedicated Engineering Project Manager (EPM) to lead a portfolio of manufacturing and data-driven software products. In this role, you will drive Apple’s manufacturing technology strategy by leading complex, cross-functional engineering initiatives with an increasing focus on AI-enabled capabilities and data intelligence. DESCRIPTION Partner with engineering, DevOps, production support, UX, data science, and AI/ML teams to deliver strategic products and features. Define technical solutions, assess feasibility, shape high-level LOEs, and develop release plans. Engage with stakeholders, business teams, and product managers to understand business goals. Convert business requirements into clear technical requirements and define end-to-end scope. Build detailed project plans, schedules, and milestones to drive high-quality delivery. Take full ownership of project outcomes. Monitor progress, identify and assess risks, and build actionable mitigation plans. Conduct regular project checkpoints and post-project evaluations to strengthen continuous improvement. Navigate complex requirements and constraints using sound judgment, adaptability, and strategic thinking. Use modern project management frameworks to manage the full software development lifecycle, breaking down work into phases, sprints, and releases.

Requirements

  • 3+ years of experience as an Engineering Project/Program Manager delivering high-quality software products.
  • Bachelor’s degree in computer science, software engineering, information systems, or equivalent experience.
  • Proficiency in both Waterfall and Agile project management methodologies.
  • Solid grasp of cloud computing concepts, data ecosystems, platform engineering, and the software development lifecycle (SDLC).
  • Outstanding verbal and written communication, including presentation skills to all levels of an organization.

Nice To Haves

  • Experience building and productizing AI-driven systems, including familiarity with AI-assisted workflows and orchestration frameworks such as MCP.
  • Strong analytical and problem-solving abilities.
  • Comfortable using data and AI-generated insights to guide decisions and communicate findings.
  • Successful track record in cross team and cross organization collaboration
  • Experience with enterprise architecture, solution design, and platform-level integration.
  • Ability to evaluate and refine engineering proposals, including AI-related solution components.
  • Master’s degree in a relevant field is a plus.

Responsibilities

  • Partner with engineering, DevOps, production support, UX, data science, and AI/ML teams to deliver strategic products and features.
  • Define technical solutions, assess feasibility, shape high-level LOEs, and develop release plans.
  • Engage with stakeholders, business teams, and product managers to understand business goals.
  • Convert business requirements into clear technical requirements and define end-to-end scope.
  • Build detailed project plans, schedules, and milestones to drive high-quality delivery.
  • Take full ownership of project outcomes.
  • Monitor progress, identify and assess risks, and build actionable mitigation plans.
  • Conduct regular project checkpoints and post-project evaluations to strengthen continuous improvement.
  • Navigate complex requirements and constraints using sound judgment, adaptability, and strategic thinking.
  • Use modern project management frameworks to manage the full software development lifecycle, breaking down work into phases, sprints, and releases.
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