cover_letter / art_n-h0D8RHeY0

Dear Apple Cloud Infrastructure Hiring Team, Apple's cloud infrastructure underpins every device, service, and developer experience the company ships — from iCloud and App Store to the on-device and server-side intelligence now central to Apple Intelligence. That intersection of massive-scale infrastructure and developer-facing platform work is where I have spent the better part of my career, and it is precisely why this role caught my attention. At Intuit, I owned the platform layer that scaled to 675M+ engagements in a single fiscal year; the engineering discipline and product instincts that work required map directly to what Apple Cloud Infrastructure demands. --- ## Technical and Platform Foundation My platform credibility runs from the infrastructure layer up to the developer experience layer. At Intuit, I led the ICE (Intuit Cloud Engineering) platform as Staff PM, scaling throughput from 6,000 to 50,000 transactions per second via an rSocket migration that supported approximately 1.5 million concurrent connections at sub-25ms TP99. That is not a metric inherited from an existing system — it required deep collaboration with distributed systems engineers, telemetry-driven prioritization using SQL and BigQuery across ~20 mobile apps and 30+ product SKUs, and a clear product roadmap that balanced reliability, developer ergonomics, and cost. The ICE Self-Service platform I delivered — DevPortal, GitOps configuration, and ICE Playground — reduced developer onboarding from two to three weeks down to minutes in pre-production and under 24 hours for production, while mitigating over $1M in projected operational expense growth. Beyond platform scale, I have hands-on experience with the infrastructure decisions that cloud PMs must reason about credibly. I led Mailchimp's GCP-to-AWS migration for microservices-as-a-service (MSaaS), delivering a Golang service template, MySQL persistence integration, and updated DevPortal documentation to meet a hard production deadline. I also initiated a Drift Detection and Resolution program — writing a Java JAR library to scan Git repositories for configuration drift and building a remediation roadmap using OpenRewrite — which required me to understand the gap between declared and actual infrastructure state at enterprise scale. On the AI and ML side, my background is substantive and recent. I hand-coded backpropagation through time in C++ in 2004 for a protein structure prediction system that became a NeurIPS 2014 publication; I rewrote that system in 2026 as a production PyTorch platform spanning 413 parameters to 8 billion — a 19-million-fold scale increase — with MLflow experiment tracking, Optuna hyperparameter optimization, and FastAPI serving across six Docker containers. My RL Workbench benchmarks GRPO, DPO, PPO, DAPO, and eight additional algorithms across TRL, VeRL, OpenRLHF, and NeMo RL frameworks with GPU Docker passthrough, live SSE metric streaming on Apple Silicon (MPS) and CUDA, and standardized throughput, memory, and convergence benchmarking. These are not survey projects — they are production systems built to answer real evaluation questions. --- ## Why Apple Cloud Infrastructure Apple's cloud infrastructure sits at a uniquely demanding intersection: it must be invisible to end users, reliable enough for hundreds of millions of devices, and flexible enough to support a developer ecosystem that spans iOS, macOS, watchOS, and now Apple Intelligence workloads. Having scaled a platform to 675M+ engagements at Intuit and built developer-facing SDKs, tooling, and self-service infrastructure from the ground up, I understand both the engineering constraints and the product discipline required to operate at that level. The opportunity to bring that experience to Apple — where the infrastructure decisions have direct consequences for every device Apple ships — is a compelling next step. --- ## Selected Relevant Experience - **Scaled ICE platform to 675M+ engagements (FY23)** across QuickBooks, TurboTax, Mint, Mailchimp, and Credit Karma; drove 275% YoY engagement growth and scaled throughput from 6K to 50K TPS via rSocket migration supporting ~1.5M concurrent connections at sub-25ms TP99. - **Delivered ICE Self-Service platform** (DevPortal, GitOps config, ICE Playground), reducing developer onboarding from 2–3 weeks to minutes in pre-production and under 24 hours for production, while mitigating $1M+ in projected opex growth. - **Led Mailchimp GCP-to-AWS MSaaS migration**, delivering Golang service template, MySQL persistence integration, and updated DevPortal documentation to meet production deadline. - **Conducted enterprise-wide Service Language Assessment** across 9 languages (Java, Python, Kotlin, Go, TypeScript, Scala, PHP, C++, Groovy), analyzing usage data and developer feedback to inform strategic language investment decisions presented to Intuit's CTO. - **Initiated MSaaS Drift Detection and Resolution program**: wrote Java JAR library to scan Git repos for configuration drift, partnered with Design on DevPortal UI, and built remediation roadmap using OpenRewrite. - **Built and shipped aeval**, a local-first AI model evaluation platform with FastAPI orchestration, TimescaleDB, Redis job queue, and Next.js dashboard — featuring bootstrap confidence intervals, Welch's t-test, Cohen's d effect size, and automated safety gates for CI/CD regression detection. - **Extended Java and Python SDK Starter Kits** with scaffolding templates, Gradle/Maven build configurations, testing frameworks, and CI/CD integration — enabling developers to go from zero to production-ready microservice in minutes. - **Led Search Service and SPL/SPL2 product ownership at Splunk**, delivering Scheduler Service end-to-end in ~4 months and achieving up to 10x query performance improvements for a Fortune 500 beta customer through mirrored topology benchmarking. --- ## Closing Apple's mission — to build technology that enriches people's lives — depends on cloud infrastructure that is reliable, scalable, and developer-friendly enough to support the next generation of Apple products and services. I have spent twelve years building exactly that kind of infrastructure, from the platform layer at Intuit to developer SDKs, telemetry-driven prioritization, and AI-native tooling. I would welcome the opportunity to bring that experience to Apple Cloud Infrastructure and contribute to the systems that make Apple's ecosystem work at scale. Thank you for your consideration. --- **O. Felix Amoruwa** famoruwa@berkeley.edu | 909-731-9011 | felixamoruwa.info