Principal AI Architect, App Store Data

Apples App Store is the worlds largest and most innovative app marketplace home to over 1.5 million apps and serving more than half a billion customers every week across all Apple devices. Since the App Store launched in 2008 it has changed how we all live; it has enabled countless new companies spawned new industries and built millions of jobs. But we believe we are just getting started. nnOur team enables data-driven innovation for internal and external partners while maintaining data quality privacy and engineering excellence as first-class citizens. nnWere looking for a highly skilled hands-on Principal AI Architect with strong software development skills and a passion for applying LLMs and Agentic workflows to real-world business problems.n

In this role you will design and ship AI systems that make App Store data useful safe and actionable from agentic workflows that automate analytical tasks to LLM-powered data products that surface insights. nnThe ideal candidate is someone who moves fluidly from prototype to production writes the code they architect and takes personal ownership of the systems they ship. They combine deep expertise in AI and distributed systems with strong product instincts excellent communication skills and genuine curiosity about data analytics workflows and they know when to use AI and when deterministic logic is the better is a high-leverage role at the intersection of data engineering AI product impact and technical leadership.n

Translate business problems and objectives into actionable AI initiatives; identify opportunities where AI can add value and create roadmaps for implementation with clear milestones and the organizationals AI strategy technology stack and framework production-grade scalable secure and efficient AI systems that reason plan and act across tools and modalities for data pipelines and enterprise AI reference architectures and reusable components covering data flows model lifecycle runtime patterns and integration emerging trends in AI and conduct proof-of-concepts (PoCs) to evaluate new closely with engineers and partner teams to build new AI-enabled data pipelines and and select the most suitable tools platforms and technologies for AI development considering factors like scalability cost and assess the performance of AI systems (quality latency drift safety and business impact). nWork on problems in an agentic context: distributed state persistence message consensus between agents (A2A) and handling non-deterministic failures in long-running loops context engineering agentic AI solutions adhere to security and compliance policies collaborate with Security Privacy and Legal teams to apply existing or develop new AI policies including sensitive data and enforce AI governance: architecture review criteria documentation standards approval procedures safety filtering and human-in-the-loop responsible AI principles including bias assessment and explainability where AI engineering standards and best practices; guide engineers on AI use cases design decisions risks and the organizations AI maturity through mentorship communities of practice and influence rather than authority.n

Bachelors degree in Computer Science Engineering or related field (or equivalent experience).nProven ability to translate business needs and ideas into scalable production-level AI ability to communicate complex technical concepts to non-technical experience with LLMs and agentic workflows MCP and A2A protocols prompt building complex agentic AI systems using LangChain LangGraph Claude Agent SDK or similar AI agent frameworks.n12 years of software engineering experience with 5 years of experience building and deploying AI/ML solutions in production environments.

Hands-on industry experience shipping LLM-powered of Prompt Injection/ Guardrail defense and secure context handling (PII redaction).nExperience with privacy regulations and compliance obligations (GDPR CCPA DMA DSA) and their impact on AI system design and data in designing scalable highly available distributed systems which can handle high data volumes.