Frontend Architect (AI Experiences), Retail and Marcom Engineering - Jobs - Careers at Apple
- Set the direction: Define the frontend AI strategy and multi-quarter roadmap across AI-powered experiences, AI-assisted engineering, and agent-ready UI foundations. Research industry trends and emerging capabilities — agent frameworks, Model Context Protocol (MCP), generative UI — and decide where we lead, where we follow, and where we wait.
- Architect the systems: Design the systems that make the strategy real — machine-readable component registries, agent-facing interfaces (MCP servers, agent-friendly CLIs), LLM-readable documentation, and the architecture behind our AI-powered tools. Keep one source of truth behind the many ways people and agents consume it.
- Represent frontend: Hold the frontend seat in cross-functional AI efforts alongside backend, infrastructure, and services architects. Connect the dots from components to application layouts, content management, data, and publishing, drive alignment where systems integrate, and partner with AI and platform teams across Apple to build on what exists rather than duplicate it.
- Make the case: Write the roadmaps, one-pagers, architecture decision records, and RFCs that guide the team — clear enough to execute without you in the room. Present, advocate, and defend direction to peers and senior leadership.
- Partner with Design: Work closely with design leadership to define generative-UI guardrails — design rules, canonical compositions, and usage validation — so AI-generated UI meets the level of detail and intent design sets.
- Scale responsibly: Start from real use cases and personas. Move quickly with focused proofs of concept, then scale with the right governance — security, privacy, evaluations, and usage telemetry — so leadership can see what's working and why.
- Drive adoption: Evangelize and champion solutions across Marcom and partner organizations, follow through on adoption, and refine tools until teams choose them rather than being told to use them.
- Multiply the team: Guide the engineers who deliver the roadmap with clear direction and thoughtful delegation, and mentor engineers across the organization. Stay hands-on with prototypes, reference implementations, and code reviews that set the bar.
- 10 years building production web applications, including 3+ years in a senior or architect role setting frontend direction across teams
- Expert-level TypeScript and React, including component architecture, server-side rendering (e.g., Next.js), schema-first data (e.g., GraphQL), and performance at scale
- Led the architecture of a design system, component platform, or shared frontend infrastructure adopted by multiple teams
- Shipped LLM-powered features or AI developer tooling to production (e.g., agentic workflows, AI-assisted code review, tool use / function calling, structured outputs)
- Hands-on daily use of AI coding agents (e.g., Claude Code, GitHub Copilot, Cursor), with a clear point of view on where they help, where they don't, and how to review what they produce
- Deep knowledge of accessibility (WCAG 2.1 AA) and how to build it into systems by default
- BS or MS in Computer Science or equivalent professional experience
- Experience designing agent-facing tooling, such as MCP servers, CLIs designed for agents, or packaged agent skills and instructions
- Experience designing APIs, schemas, or component metadata that models generate against
- Experience defining evaluation strategies for AI systems — evals, golden datasets, LLM-as-judge scoring, and regression gates
- Experience designing how AI agents operate in CI/CD — AI-assisted code review, automated releases, or agentic feature development with quality gates and human review
- Understanding of AI security and governance, including least-privilege agent permissions, prompt injection, and privacy-preserving telemetry
- Familiarity with design tokens, theming, and generative-UI approaches that keep AI-generated interfaces on-brand
- A record of published architecture decisions, RFCs, or white papers that influenced direction across an organization
- Experience in large, multi-team enterprise environments, navigating governance, security review, and cross-org dependencies
- Experience working in environments with ambiguity — defining strategy as the underlying AI capabilities evolve
- Track record of setting technical direction and building alignment across competing priorities, with excellent written and verbal communication, including presenting architectural trade-offs to engineering and executive audiences
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Required Skills
Required Languages
🇬🇧 English