Sr. Engineering Program Manager, Human Centered AI (HAI), Apple Services Engineering - Jobs - Careers at Apple
- Strategic Leadership: Partner with engineering, research, and senior leadership to shape technical roadmaps, influence investment decisions, and drive organizational priorities.
- AI Evaluation and Responsible AI: Advance evaluation strategies for LLMs and agentic AI systems, including LLM-as-a-Judge, automated evaluation, human evaluation, model reliability, and AI safety.
- Cross-Functional Leadership: Lead complex initiatives across AI research, engineering, infrastructure, and safety. Build trusted relationships, navigate competing priorities, and influence decisions without direct authority.
- Program Strategy and Execution: Drive large-scale AI/ML initiatives, establish measurable outcomes, identify risks and dependencies, and ensure alignment with organizational objectives.
- EPM Excellence and Innovation: Mentor EPMs, establish scalable program management practices, and leverage Generative AI and automation to improve organizational efficiency.
- Executive Communication: Translate complex technical challenges into clear recommendations, communicate strategic tradeoffs, and drive informed decision-making with senior leadership.
- 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.
- 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.
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Required Languages
🇬🇧 English