# June Kim

june@june.kim · 604 356 1191 · www.june.kim · kimjune01

## Summary

Applied AI Engineer specializing in RAG pipelines, agentic workflows, and LLM-powered data systems. 10+ years of software engineering at Google, Loom, and high-growth startups. Builds production AI systems that ship.

## Work Experience

### Independent Contractor — Applied AI Engineer
**2025 — present**

- **Anyteam.com:** Designed and shipped an accessibility data pipeline for the Sales OS and a browser-extension-based web scraper to ingest and retrieve domain knowledge via Retrieval-Augmented Generation.
- **Buildbetter.ai:** Built 4 third-party integrations (Circle.so, Notion, Front, Attio) with incremental sync, OAuth2 flows, and deduplication, expanding the platform's customer data ingestion surface.
- Developed AI-powered field classification system using LLMs to automatically map import columns with confidence scoring, and prototyped custom AI agents for customer signal analysis.
- Shipped CI/CD quality gates, E2E testing infrastructure, and reusable developer tooling (Claude Code skills for log querying, migration gen, CI failure analysis).

### Littlebird — Applied AI Engineer
**Sep 2024 — May 2025**

- Designed and implemented agentic data ingestion pipelines, utilizing LLM-based condensation (Claude, GPT-4, Gemini Flash) and deduplication to reduce noise by 90%, directly improving RAG retrieval accuracy and chat grounding.
- Architected macOS and Chrome integrations (Swift, Tauri, Rust) using Accessibility APIs to enable real-time context injection for AI agents.
- Developed core Python backend services for prompt orchestration and object deduplication, leading infrastructure migrations with zero user downtime.
- Built end-to-end RAG pipeline: filtered, extracted, parsed, and condensed unstructured desktop accessibility data into a searchable vector store.

### Loom — Senior Software Engineer
**Mar 2022 — May 2023**

- Optimized core video infrastructure, increasing system reliability from 97% to 99.7% via multiresolution UI implementations and Shaka Player interfacing.
- Architected a full TypeScript refactor of the Electron desktop app, reducing maintenance overhead and improving cross-platform performance.

### YouTube / Google — Software Engineer
**Jun 2019 — Mar 2022**

- Independently contributed to front-end features promoting YouTube Premium subscriptions, using C++ and Objective-C.
- Directed the launch of a high-visibility Premium sign-up framework, resulting in a 2% lift in conversion rates impacting 50M+ users.
- Conducted dozens of technical interviews for L3/L4 engineering candidates, helping scale the Music & Premium organization.

### Earlier Experience

- **Loop Now Technologies (Firework)** — React Native & iOS Engineer (2018–2019). Built cross-platform UI features; patented video view technology.
- **Lipsi Technologies** — Senior iOS Developer (2016–2018). Scaled anonymous messaging app to #1 Lifestyle on App Store USA and 2.3M users.
- **Nano 3 Labs / Lighthouse Labs / Camvy** (2013–2015). iOS development, AR prototyping, teaching, full-stack Rails.

## Education

**Bachelor of Science** — Simon Fraser University (2015–2017)
Machine learning, computer vision, data structures & algorithms, databases, networking, security

**Bachelor of Business Administration** — Simon Fraser University (2008–2012)
Product management, strategy, operations, entrepreneurship

## Skills

**AI/ML:** RAG, LangChain, Agentic Workflows, Prompt Engineering, Vector Databases, Embeddings, Tool Use / Function Calling, LLM Evaluation, Model Context Protocol (MCP)
**Models & APIs:** OpenAI (GPT-4), Anthropic Claude, Google Gemini
**Languages:** Python, TypeScript, C/C++, Swift, Rust
**Infrastructure:** FastAPI, CI/CD, Git/GitHub, Claude Code