AI Product Manager with experience across the full product lifecycle—from ideation and user research to deployment and adoption at both fast-moving startups and Fortune 500 scale. Built and shipped LLM, RAG, and generative AI products serving 3.5M+ DAUs and $1B+ in business value.
Get to know me better
I've been in AI since 2021—six years across disability tech, a mobile app development company, early-stage pre-funded startups, scaled bootstrap ventures, and giants like Boeing. I've also TA'd LLM courses at the University of Washington and built my own startup experiments along the way.
My titles have often said ML Engineer or Data Scientist, but the work has always been product-shaped: I've ideated, planned, and shipped end to end—roadmaps, user research, prototypes, and production deployments—not just models behind the scenes. That means real comfort with both 0→1 (scrappy MVPs, founder rooms, first users) and 1→100 (adoption at scale, stakeholder alignment, enterprise rigor).
The hardest part of AI today isn't learning one framework—it's keeping up with how fast the field moves. That's where I do my best work: spotting the right problem, shaping a practical solution, and knowing which tools are actually worth using this month—not last year.
I'm passionate about the next wave of AI products—not incremental features, but transformative experiences that feel magical yet deliver concrete ROI. Currently exploring AI Product Management roles where I can leverage both technical depth and product instincts.
My career journey and achievements
Graduate program in advanced statistical methods, machine learning, and data engineering with focus on generative AI and neural networks.
Undergraduate degree in Computer Engineering with focus on software development, algorithms, and computer systems.
Some of my recent work
Oct 2025 – Dec 2025 | Personal Research Project · 26★
Production-grade microservices platform for intelligent LLM routing with ONNX-based intent/complexity classification via DistilBERT, PII guardrails, A/B testing, and Prometheus/Grafana observability. OpenAI-compatible drop-in API reduces inference costs 40–60%. Open-sourced with active external contributors.
Oct 2025 – Jan 2026 | Personal Research Project
Built GeoniusAI, an enterprise-grade AI visibility SaaS with a proprietary Visibility Score combining AEO, GEO, and brand metrics across ChatGPT, Gemini, and other AI tools. MCP kit orchestrates 30+ SEO APIs via LangGraph multi-agent architecture with human-in-the-loop middleware. Full-stack solo execution from Figma → Cursor → Vercel.
Dec 2025 – Present | Personal Research Project · 7★
Developing a 2-line persistent LLM memory library using Mem0 + interceptor architecture (inspired by mem0 and memori). Zero-code integration that injects relevant memories before LLM calls and extracts new memories after conversations—works with OpenAI, Anthropic, LiteLLM, and 100+ models.
Built advanced meta-analysis tools using statistical modeling and machine learning to synthesize research findings and generate insights from large-scale datasets.
Created an intelligent content generation system using RAG architecture and agentic AI frameworks to produce engaging social media posts and marketing content. Also developed fine-tuned language models for generating creative and effective marketing slogans, utilizing advanced NLP techniques and prompt engineering.
May 2025 – Oct 2025 | Volunteer — corporate training firm
Built resume intelligence tool parsing 2,000+ resumes with Gemini LLM and Supabase VectorDB, using advanced RAG techniques, hybrid semantic/rule-based matching, and Google Drive API integration at near-zero infra cost.
Volunteer project for a corporate training firm
Developed comprehensive data analytics solutions for enterprise storage systems, implementing advanced ML models for performance optimization and predictive analytics.
Capstone project, report proprietary to organization
Let's collaborate and create something amazing
Seattle, WA, USA