Software Engineer - Regulatory AI & Connected Data

Apple is a leading technology company that ensures its products meet the highest standards of regulatory compliance, product safety, and analytical rigor. The Software Engineer will design, build, and ship AI-powered software systems to improve the efficiency of the Product Analysis and Compliance Engineering (PACE) team, collaborating closely with domain experts and utilizing data to guide development.

Responsibilities:

• Design, build, and ship AI-powered software systems that improve team efficiency, delivering incrementally and iterating based on user feedback
• Apply secure engineering practices throughout: secrets management, data classification, access control, and audit logging appropriate for compliance-sensitive data
• Build and maintain robust data pipelines that connect corporate data sources, ensuring data quality, lineage, and accessibility
• Effectively use & improve leading agentic harnesses to build software with your principles, through the development of skills, agents and MCPs
• Integrate AI and large language models into production systems with appropriate evaluation, guardrails, and monitoring - treating models as components, not magic
• Ensure that there is an audit trail for traceability/lineage for AI/LLM based decisions
• Establish and maintain continuous delivery pipelines, optimizing for the DORA metrics: deployment frequency, lead time, change failure rate, and mean time to recovery
• Build observability into every system from day one - instrumentation, structured logging, alerting, and dashboards that give the team confidence to ship fast
• Write clean, testable, well-factored code; practice continuous integration, continuous refactoring, and small batch delivery as daily habits
• Actively explore the PACE team’s domain, emerging tools, and adjacent problem spaces - bring new ideas and challenge assumptions
• Work directly with PACE team’s domain experts to understand problems deeply before building solutions
• Collaborate across teams and organizations to integrate data sources and align on technical direction
• Contribute to the engineering culture of a new team - shaping practices, running retrospectives, and helping the team continuously improve
• Represent your work through demos, design discussions, and clear written communication