Full Job Description
Apple's Sales organization generates the revenue needed to fuel our ongoing development of products and services. Our World Wide Sales Business Transformation group focuses on implementing strategies, programs, tools, and processes that enable the business to drive sales, improve customer experience, and innovate the way we lead and support one of the largest channel operations in the world. As part of our World Wide Sales Business Transformation group, you will play a critical role in the execution and delivery of AI initiatives that enable the business to drive sales, improve customer experience, and innovate one of the largest channel operations in the world.
We are seeking a highly organized and technically fluent AI Engineering Program Manager to drive the execution of complex AI/ML projects. In this role, you will be the driving force behind our engineering delivery, ensuring that sophisticated AI solutions-such as conversational agents, RAG systems, and automated workflows-are built and deployed successfully. You will partner with Product Managers, Data Scientists, AI Engineers, and Security teams to break down complex product roadmaps into actionable engineering milestones, manage cross-functional dependencies, and clear roadblocks to ensure technical excellence and on-time delivery.
Description
In this role, you will:
-Drive the end-to-end execution and delivery of key AI and ML platforms supporting the Sales teams - including but not limited to Security, CSO, Change, and PMO teams.
-Partner closely with Product Management to translate product strategy and roadmaps into detailed engineering execution plans, sprint schedules, and deliverable milestones.-
-Manage complex cross-functional dependencies across Software Engineering, Data Science, UX/UI, Enterprise Architecture, and Information Security teams.
-Proactively identify, track, and mitigate execution risks, technical blockers, and resource constraints before they impact project timelines.
-Facilitate engineering planning, daily stand-ups, technical design reviews, and sprint retrospectives to ensure team alignment and momentum.
-Track the integration of technical components, such as LLM APIs, data pipelines, and microservices, ensuring all technical moving parts align for seamless deployment.
-Serve as the central point of contact for project status, distilling complex engineering progress into clear, concise executive updates for business partners and leadership.
-Establish and continuously improve engineering delivery processes, fostering a culture of efficiency and collaboration within a fast-paced, dual-speed organization.
-Possess the technical depth to understand AI Proof of Concepts (POCs) written in Python, enabling you to engage deeply in technical design discussions and validate scalability with the engineering team.
-Drive the program delivery of MLOps best practices, ensuring engineering teams stay on track to implement version control, CI/CD pipelines, automated testing, and production monitoring for AI systems.
Minimum Qualifications
Typically requires 8+ years of experience in Engineering Program Management, Technical Project Management, or a related role within software engineering or data organizations.
Proven track record of managing complex, distributed enterprise software or data-driven products.
Strong technical fluency and the ability to understand architectural diagrams, API integrations, and software development life cycles (SDLC).
Technical proficiency with Python, including the ability to read code, evaluate technical Proof of Concepts (POCs), or run basic scripts to support data-driven program management and decision making.
Familiarity with artificial intelligence, machine learning concepts, and LLM ecosystems (GenAI, RAG, prompt engineering) to effectively communicate with highly technical teams.
Exceptional organizational skills and expertise in agile methodologies and project management tools (e.g., Jira, Confluence, Wrike, or similar).
Outstanding communication and presentation skills, with the ability to translate technical jargon into business impact for executive stakeholders.
Ability to lead through influence, building strong relationships across matrixed technical and non-technical teams.
Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
Preferred Qualifications
Background in sales analytics, go-to-market strategies, or sales operations.
Direct experience managing the deployment of Machine Learning models or AI applications into production environments.
Understanding of data privacy, enterprise security reviews, and compliance requirements related to AI and data governance.
Familiarity with cloud infrastructure, microservices, and CI/CD deployment processes to better anticipate engineering timelines.
PMP, CSM, or related program management certifications.
Master's degree in Engineering, Computer Science, or a related technical field preferred.
