Senior Software Engineer - 8 Years at Apple

James Kelly

Senior Software Engineer

San Diego, CA ● ***************@*****.*** ● 929-***-**** ● Linkedin SUMMARY

Senior software engineer with 8 years of experience at Apple, designing and delivering high scale web Apps, internal tools, and developer platforms. Expert in full stack development (Python, Go, Node.js, TypeScrip, React) and integrating LLMs into production systems. Proven track record of improving developer velocity, reducing latency, and leading cross functional initiatives in highly confidential environments. PROFESSIONAL EXPERIENCE

Apple

Senior Software Engineer 07.2018 – Present

Led web development across the Games System Team, App Store web portal, and internal ML tooling. Delivered 6+ major projects, mentored 6 junior engineers, and worked on unreleased features under strict NDA.

● Game Center real time dashboard (2024 – Present):

-Designed a real time matchmaking dashboard using React and TypeScript with Node.js, backed by PostgreSQL and Redis, supporting thousands of daily internal users

-Implemented backend services in Go for matchmaking state management, caching, and real time data delivery

-Established a WebSocket based live leaderboard viewer with React and Go microservices, enabling real time game session visibility and reducing QA debug time by 35%

-Fine tuned a Llama 3 8B model to summarise server logs, cutting mean time to resolution (MTTR) for a class of common incidents from 20 to 4 minutes in controlled testing.

● App Store web portal rewrite (2022–2024):

-Rewrote App Store web app detail and search pages using Next.js and TypeScript, improving mobile performance to Lighthouse 98+ via ISR, code splitting, and lazy loading

-Developed backend APIs and middleware in Go for traffic shaping, caching, and request validation.

-Established ML-powered review summarisation service in Python using distilled BERT with ONNX Runtime, generating pros and cons summaries and increasing engagement by 12%

-Deployed services on Kubernetes with autoscaling and observability, improving reliability under peak traffic

● RAG system for internal developer portal (2023–2025):

-Created a retrieval augmented generation system (Python/FastAPI, React, Apple’s Core ML, Milvus, Redis) enabling natural language queries over engineering docs.

-Fine tuned a CodeLlama 7B model on a curated set of Swift/Objective C codebases, reducing hallucination rate from 18% to 4% (measured by internal factuality scoring).

-Deployed as a Slack bot and web UI serving 2,000+ queries per week, estimated to save 150 engineering hours monthly.

● Apple Maps Web Beta (2020–2022):

-Developed the place card component and search autocomplete (React, TypeScript, Node.js, Python, PostGIS).

-Implemented a service worker caching strategy that improved repeat visit load time by 45%.

-Wrote Python scripts to transform internal map data to GeoJSON, reducing sync errors by 70%.

● Game Matchmaking Configuration UI (2019–2021):

-Created a configuration UI (React, Redux, Node.js, PostgreSQL, Docker) that cut developer setup time from days to hours.

-Added real time validation preventing 99% of misconfigurations. Integrated a Go based rule simulator used by 25+ internal game teams.

● Legacy Ruby on Rails to Node.js migration (2018–2019):

-Spearheaded migration (Node.js, TypeScript, React, PostgreSQL) reducing page load times from 3.2s to 0.9s.

-Wrote Python data migration scripts ensuring zero data loss for 10M+ records.

-Built a feature flag system (Node.js + Redis) enabling gradual rollouts with 100% team adoption within 3 months and no downtime.

Across all projects, led LLM integration efforts including prompt engineering and fine tuning of open source models (Llama 3, CodeLlama, BERT) using PyTorch and Hugging Face. Built end to end RAG pipelines with LangChain and vector stores (Milvus, Pinecone). Optimized LLM inference latency using ONNX runtime and Redis caching. Designed A/B testing and hallucination detection metrics (BLEU, ROUGE, custom factuality score).

SKILLS

● Languages: Python, Go, TypeScript, JavaScript, Bash

● Frameworks & Libraries: React, Node.js, Next.js, FastAPI, LangChain, Redux

● Databases & Storage: PostgreSQL, Redis, Milvus, Pinecone, DynamoDB

● Infrastructure & Tools: Docker, Kubernetes, Git (GitHub, GitLab), GitHub Actions, Cursor, GitHub Copilot, HAProxy, ElastiCache, Google Kubernetes Engine

● Architecture & Practices: Microservices, API first design, Domain Driven Design, Service Oriented Architecture, Observability, Design Reviews & RFC Process, SLO/SLA driven engineering

● ML & LLM: Large Language Models, Retrieval Augmented Generation, Prompt Engineering, Model Serving

(ONNX runtime), Fine tuning (PyTorch, Hugging Face), ML Pipelines, Feature Stores

● Testing: Unit & integration testing (Jest, PyTest), load testing, A/B testing frameworks

● Other: WebSocket, Redis Streams, Protocol Buffers, OpenAPI, GitLab CI/CD Large Language Model, AI, LLM, Chatgpt, Java, Kotlin, Gemini. Domain-Driven Design, Service-Oriented Architecture, Infrastructure as Code, Reliability-Centered Design, Architectural Decision MakingDjango, Fast API, Flask, HAProxy, TPUs/AI accelerators, Authentication & Authorization, DynamoDB, Linux, Windows, object-oriented programming, github, Gitlab, GitHub Actions, Cursor, Github Copilot, ElastiCache, Elastic Beanstalk, Google Kubernetes Engine, Large Language Models, Retrieval-augmented generation, Observability, Cloud-Native Architecture, Scalability Engineering, ML Infrastructure, Model Serving Systems, Experimentation Platforms, Data Pipelines, Feature Engineering Systems,DataFrame APIs, Vectorized Inference, Apache Flink, RabbitMQ, Elasticsearch, Microservices Decomposition, API-First Design,IaC, Design Reviews & RFC Process, SLO/SLA-Driven Engineering Model Serving Inference Optimization MLOps ML Pipelines Feature Stores Experimentation Platforms AI Platform Engineering Prompt Engineering AI Observability val-Augmented Generation JDA/Blue Yonder WMS/WLM MS SQL Database Server MIS Shopify Neo4j, JUnit, Karma, Jasmine, Spectator, Cypress, Spring Boot, Webflow, Webpack Apex, Lightning Web Confluent Cloud Components (LWC), Salesforce Crossplane HashiCorp Cloud Native Landscape CNCF Healthcare Fintech Protocol Buffers, RAML, Swagger, OpenAPI, AI Observability, Vectorized Inference, Cloud Native Architecture, Scalability Engineering, IaC (Terraform/Crossplane), EDUCATION

● Rochester Institute of Technology

M.S. Computer Science 2016 – 2018

B.S. Computer Science 2012 – 2016

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