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