Tools and Automations Lead, App Review

Apple•Cupertino, CA

About The Position

Apple’s Worldwide Developer Relations team (WWDR) provides services, resources, and guidance to empower the global developer community to innovate and bring app ideas to Apple’s platforms. The App Review team operates at a massive scale, and its effectiveness relies on the people, tooling, automation, and intelligence developed. This role is for a highly technical individual who views App Review’s process and policy application as a system to be designed, measured, refined, and continuously improved. The ideal candidate is comfortable prototyping solutions and defining requirements for engineering partners to build at scale. This is a hands-on role for someone who is an engineer, systems thinker, and process designer, with strong cross-functional collaboration skills. You will identify gaps in current workflows for review specialists, developers, and Apple, then design, prototype, and deliver solutions, increasingly leveraging generative AI. You will determine what to build yourself and what to delegate to engineering partners, ensuring those partnerships are successful. You will act as a liaison between App Review’s operational reality and product, AI, and platform engineering capabilities, translating operational processes into requirements and ensuring specialists trust and use the tools developed. You will own the design and delivery of internal tooling and automation for the end-to-end App Review experience, supporting specialists, developers, and Apple’s policy and operational standards. The role involves automating manual workflows, improving data-driven decision-making, and ensuring consistent policy application at scale. You will also be responsible for knowing when to build solutions internally and when to collaborate with platform and infrastructure teams, ensuring the development of durable, high-reliability infrastructure. You will prototype ideas, translate them into clear requirements, and enable partner teams to build production systems. This involves partnering with App Review specialists, leadership, and policy stakeholders to understand operational challenges and identify areas for improvement through automation or better interfaces. You will build prototypes and solutions directly, such as Swift apps or data evaluation scripts, to demonstrate value and de-risk investments. Close collaboration with Apple Services Engineering platform teams and AIML platform teams is crucial, defining technical requirements for stable, reliable infrastructure. You will make strategic build-vs-partner decisions, handling lightweight, exploratory work internally and routing systems requiring long-term reliability and scale to appropriate engineering partners. You will advance the automation and AI agenda by designing and deploying GenAI and agent-based solutions (LLMs, RAG, agents) to augment review, surface risk, and reduce manual effort. You will build prototypes yourself when appropriate and make deliberate AI build-vs-partner decisions, understanding when off-the-shelf LLM calls suffice and when Apple’s AIML platform teams are needed. Strong UX and workflow design skills are essential, ensuring tools are intuitive, fast, and trusted. Driving adoption through iteration based on user feedback and outcomes is key. You will define success metrics, instrument solutions, and iterate based on usage and results. Clear communication of designs, trade-offs, and results to both technical and non-technical audiences is required.

Requirements

7+ years of combined experience across software engineering, data engineering, solutions engineering, or technical product roles.
Demonstrated ability to take a problem from ambiguous need to working solution — including building the prototype yourself, not only specifying it.
Proven track record of effective cross-functional collaboration with platform or infrastructure engineering teams, including writing the requirements that enable partner teams to deliver.
Strong proficiency in Python and modern data tooling; ability to build standalone solutions.
Hands-on experience designing and deploying GenAI/agentic solutions (RAG, LLMs, agents) — and a tinkering mindset that stays current with what is actually shipping, not just what was state-of-the-art a year ago.
Strong product instincts: an eye for UI/UX, workflow design, and the human factors that determine whether a tool gets used.
Demonstrated ability to produce clear architectural diagrams and technical documentation for non-technical stakeholders.
Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Experience operating at the intersection of policy, operations, and engineering — building systems that apply rules and standards consistently, at scale.
Excellent problem-solving, analytical, and written/verbal communication skills.
Self-directed and proactive, with demonstrated creative and critical thinking; able to manage multiple efforts simultaneously.
Strong cross-functional collaboration and influencing skills.

Nice To Haves

Familiarity with App Review, trust and safety, content moderation, or comparable operational review domains.
Experience integrating with internal platform and AIML services, and a clear understanding of when to prototype versus when to invest in partner-built infrastructure.

Responsibilities

Partner with App Review specialists, leadership, and policy stakeholders to understand how review actually happens, where it breaks down, and where automation or better interfaces would meaningfully improve quality, consistency, and throughput.
Build prototypes and solutions directly — from a Swift app that integrates with a platform API to scripts that evaluate data or run a process-automation task — to prove value quickly and de-risk the larger investment.
Work closely and credibly with Apple Services Engineering platform teams, AIML platform teams, and other cross-functional partners, defining clear technical requirements that enable them to build stable, reliable, production-grade infrastructure on our behalf.
Make the right build-vs-partner call: own the lightweight, fast-moving, and exploratory work yourself, and route the systems that demand long-term reliability, scale, and operational ownership to the right engineering partners.
Advance our automation and AI agenda — designing and deploying GenAI and agent-based solutions (LLMs, RAG, agents) that augment review, surface risk, and reduce manual effort.
Build the prototype yourself; ship it where shipping it yourself is the right call.
Make the AI build-vs-partner call deliberately: know when an off-the-shelf LLM call is enough, when a problem needs Apple's AIML platform teams behind it, and translate cleanly in both directions so each side can do its job well.
Bring a strong sense of UX and workflow design: the tools you create or specify should be intuitive, fast, and trusted by the people who depend on them daily.
Drive adoption, not just delivery. Sit with the specialists who use what you ship, watch where it falters, and iterate.
Define how success is measured, instrument your solutions, and iterate based on real usage and outcomes.
Communicate designs, trade-offs, and results clearly to both technical and non-technical audiences, including leadership and engineering partners.