Principal AI Architect, App Store Data

Apple Apple · Big Tech · Cupertino, CA +1 · Software and Services

Principal AI Architect role focused on designing and shipping AI systems, including agentic workflows and LLM-powered data products, for the App Store. The role involves translating business problems into AI initiatives, guiding AI strategy, designing production-grade AI systems, and ensuring adherence to security and compliance policies. Requires extensive experience with LLMs, agentic workflows, and building/deploying AI/ML solutions in production.

What you'd actually do

  1. Design production-grade scalable, secure, and efficient AI systems that reason, plan, and act across tools and modalities for data pipelines and applications.
  2. Work 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 memory.
  3. Ensure 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 handling.
  4. Establish and enforce AI governance: architecture review criteria, documentation standards, approval procedures, safety filtering, and human-in-the-loop mechanisms.
  5. Apply responsible AI principles including bias assessment and explainability where appropriate.

Skills

Required

  • LLMs
  • Agentic workflows
  • Prompt engineering
  • LangChain
  • LangGraph
  • Claude Agent SDK
  • Software development
  • Distributed systems
  • Data engineering
  • AI/ML production deployment
  • Security and compliance policies
  • Responsible AI principles
  • Bias assessment
  • Explainability

Nice to have

  • Prompt Injection defense
  • Guardrail defense
  • Secure context handling
  • PII redaction
  • GDPR
  • CCPA
  • DMA
  • DSA
  • Scalable distributed systems
  • High data volumes

What the JD emphasized

  • Proven ability to translate business needs and ideas into scalable, production-level AI solutions.
  • Extensive experience with LLMs and agentic workflows, MCP and A2A protocols, prompt engineering.
  • Experience building complex agentic AI systems using LangChain, LangGraph, Claude Agent SDK, or similar AI agent frameworks.
  • Hands-on industry experience shipping LLM-powered products.
  • Experience with privacy regulations and compliance obligations (GDPR, CCPA, DMA, DSA) and their impact on AI system design and data architecture.

Other signals

  • design and ship AI systems
  • LLM-powered data products
  • agentic workflows
  • production-grade scalable AI systems