Sr. Engineering Program Manager, Human Centered AI (HAI), Apple Services Engineering

At Apple, we believe in the power of innovation to improve lives. Here, your ideas can quickly become impactful products, services, and customer experiences.

The Human-Centered AI (HAI) team within Apple Services Engineering is seeking an experienced Staff Engineering Program Manager to drive strategic initiatives across AI research, engineering, evaluation, and Responsible AI.

In this role, you will partner with engineering, research, and senior leadership to shape technical strategies, influence priorities, and advance scalable approaches to evaluating AI quality, reliability, and safety. You will bring expertise in modern AI evaluation methodologies, including LLM-as-a-Judge, automated evaluation, and human evaluation.

We are looking for a strategic leader who brings technical insights, challenges assumptions, navigates ambiguity, and drives alignment across complex organizations. You will also help strengthen Engineering Program Management practices through mentorship, scalable frameworks, and innovative applications of Generative AI.

Minimum Qualifications

• 8+ years of experience in engineering or technical program management, leading complex cross-functional initiatives.

• Strong technical understanding of AI/ML systems, including generative AI and large language models.

• Experience with AI evaluation methodologies, including LLM-as-a-Judge, automated evaluation, and human evaluation.

• Understanding of Responsible AI principles, including safety, reliability, and risk assessment.

• Demonstrated ability to influence technical strategy, navigate ambiguity, and drive alignment across engineering and research organizations.

• Excellent communication, analytical, and problem-solving skills, including experience engaging senior leadership.

• BS in Computer Science, Engineering, or a related technical field, or equivalent industry experience.

Preferred Qualifications

• Experience with foundation models, LLMs, or agentic AI systems at scale.

• Deep understanding of evaluation methodologies, including judge calibration, benchmark design, synthetic data, and evaluation infrastructure.

• Experience with AI safety, adversarial testing, red teaming, and Responsible AI practices.

• Experience translating AI research into scalable engineering solutions.

• Experience mentoring EPMs and establishing scalable PMO practices.

• Experience leveraging Generative AI or automation to improve program management efficiency.

• Demonstrated ability to influence technical roadmaps, investment decisions, and senior engineering leadership.