Schwannden Kuo
Tech Lead, Identity & Applied AI
Professional Summary
Tech lead with a decade across data products, identity platforms, and applied AI. Currently leading SSO subsystem at Ubiquiti serving millions of active users under high-throughput production load, and built the team's portfolio of production AI agents — multi-agent triage, release monitoring, code review — that learn from each use. Previously Director of ML at MoBagel, where I won the enterprise accounts (Chunghwa Telecom, Wistron, AUO) that anchored Series A revenue and re-architected the AutoML engine for ~30× runtime efficiency. Author, speaker, open-source contributor.
Work Experience
SSO Team Lead
Ubiquiti • Aug 2025 - Present
- • Built and shipped a suite of production AI tools for the SSO team, including a multi-agent release monitor and a read-only incident-triage agent that reduced alert-to-root-cause time by 70%. Additionally developed team-shared agents for feature development and code review to improve consistency in delivery quality and velocity.
- • Led a multi-quarter API latency initiative to completion by optimizing caching strategies, identifying performance bottlenecks, and refactoring deployment architecture. Achieved a 90–97% reduction in P95 latency across six critical auth/MFA endpoints (e.g., login: 11.27s → 0.79s; email MFA: 10.18s → 0.31s; password reset: 9.27s → 0.54s) while reducing compute capacity requirements by over 60%.
- • Owned cross-team architectural delivery for the SSO platform, leading the end-to-end implementation of "Bring Your Own IdP" (SAML/OIDC for Entra, Okta, and Google Workspace). Successfully managed the project from initial design through early access and full customer adoption, despite having no prior experience with these protocols.
Cloud Software Engineer
Ubiquiti • Aug 2024 - Aug 2025
- • Velocity: reduced feature lead time ~30% and accelerated security patching ~5× by revamping the release lifecycle and automating consistency checks.
- • Resilience: diagnosed a 30-minute production login p95 spike (5.19s vs 1.5s baseline) as a Postgres row lock held across PBKDF2/Argon2 hashing; 15-LOC fix achieved a 697× improvement in mean exec time on hot-row updates.
- • Resilience (DB): engineered high-availability database architecture with strict read/write separation, eliminating production impact during RDS replica events.
- • Operated AWS SSO at millions of active users under high-throughput production load, aligning security architecture with business outcomes and reducing support cost.
Senior Software Engineer
Dell • Jan 2023 - Aug 2024
- • Modernized a legacy integration test platform into a cloud-native architecture (AWS & Kubernetes), reducing operational costs by 50% and accelerating product build time by 400%, directly improving time-to-market.
- • Advocated for developer-first practices by gathering feedback from engineering teams and influencing CI/CD adoption (GitHub Actions, Argo, Kustomize, Helm).
- • Established cloud security best practices (automated vulnerability scanning, SBOM, Trivy) to align engineering efficiency with enterprise compliance.
Senior Software Architect
MoBagel • Sep 2021 - Dec 2022
- • Architected 8ndpoint.com, the AI-driven advertising platform whose technical assets and customer traction anchored MoBagel's strategic M&A acquisition; integrated generative personalization for campaign engagement.
- • Led the migration of core services to a hybrid-cloud environment, designing scalable IAM and network structures across GCP (GKE, Cloud SQL, BigQuery) and AWS (EC2, S3, VPC) utilizing orchestration tools like ArgoCD and Airflow.
- • Partnered with product leadership to translate complex AI/ML capabilities into customer-facing benefits, effectively bridging the gap between R&D innovation and enterprise campaign ROI.
Director of Machine Learning
MoBagel • Jun 2018 - Sep 2021
- • Won three Taiwan enterprise accounts that anchored Series A revenue thesis — Chunghwa Telecom, Wistron, and AUO; two became strategic investors. Each engagement combined direct customer ownership with the technical solution: re-architected the general AutoML engine (Scala / Hadoop) for memory and compute efficiency to ship to Chunghwa Telecom — ~30× runtime improvement; designed bespoke algorithmic solutions for Wistron and AUO industrial problems with measured ROI per engagement.
- • Built the engineering organization from the ground up as hiring manager — interviewed and onboarded engineers across QA, DevOps, Web, and Algorithm functions; coached the Frontend Lead and Algorithm Team Lead through their first 12 months; transitioned the QA function to a hired QA Lead.
- • Restructured the product to enable an "inner-source" culture across teams, accelerating feature rollout ~4×.
Senior Data Scientist
MoBagel • Jun 2017 - Jun 2018
- • Automated machine learning design and reactive machine learning architecture with Scala, Akka, Spark.
- • Design and implement the first generation AutoML system, achieve 300x speed up to secure key accounts.
Software Developer
University of Pittsburgh • Jun 2016 - Sep 2016
- • Integrate latest statistical methods in -omic study to build user friendly application for biostatisticians. Create open source project, to encourage open source collaboration and accelerate impact. Train researchers to maintain the project.
- • Publish paper on biostatistics (See publications).
Research Assistant
Academia Sinica • Jul 2014 - Jul 2015
- • Assist research in NDN network. Open sourced project (source code and book) to deploy NDN on Galileo. Featured in intel maker community.
Speaking Highlights
AI Agentic Development & Harness Engineering
Three-hour training across three parts. Part 1: paradigm shift to harness engineering — context engineering, skills as durable assets, the four eras of AI development. Part 2: bootstrapping the AI workflow — pre-commit/CI as agent sensory organs, skill authoring, plan-driven feature development. Part 3: provider-agnostic harness — portable artifacts (AGENTS.md, skills, MCP) across Claude, Codex, Cursor, and Gemini.
Audience: MoBagel core developer team and agentic AI team (~15 engineers)
End‑to‑End AutoML in Practice (Decanter AI)
Practical AutoML pipeline design, speed/accuracy trade‑offs, and real‑world deployments
Audience: Industry practitioners and partners; workshop attracted hundreds of participants
AIoT and Data Analysis: Approaching Industrial AI
Key principles of 'ML Done Right' including speed/accuracy trade-offs, evaluation vs. implementation cost, human vs. machine decision-making, and real-world case studies
Audience: Industry practitioners, partners, academics
Statistical Machine Learning Workshop (Campus‑wide)
Intuitive approaches to high‑dimensional statistics for engineering students; emphasized how statistical thinking underpins modern AI/ML
Audience: Students
And 3 more speaking engagements...
Technical Skills
Cloud & DevOps
Languages & Frameworks
Data & ML
Publications & Writings
Explore my technical publications, speaking engagements, and thought leadership contributions spanning cloud native technologies, AI/ML, and DevOps.
View Speaking & PublicationsOpen Source Contributions
View all contributions →Research Tools
Community Projects
Educational documentation site for building autonomous AI agents using Claude
+1 more features
And 1 more community projects...
Active contributor to various open source projects in the cloud native, Python, and DevOps ecosystems.
Education & Volunteer Experience
Education
Master's Degree
National Chiao Tung University • 2017
- • Teaching Assistant for queueing theory, machine learning, and formal language
- • Organizer and Speaker for 2017 NCTU Statistical Machine Learning Workshop
Bachelor's Degree
National Chiao Tung University • 2015
Volunteer Experience
Teacher for Special Kids (陪讀老師)
樂服社區關懷協會 - 兒少據點 • Aug 2017 - Feb 2019
Help kids on their homework, but most importantly just being there and let them know someone does care and love them.