Samuel Huang
@samuelhuang
Staff Software Engineer building AI/infra telemetry, observability platforms, and developer productivity tooling.
United StatesWhat I'm looking for
I’m a Staff Software Engineer with 10+ years designing and scaling full-stack platforms, distributed systems, cloud-native infrastructure, developer productivity tooling, and data-intensive web applications. I lead cross-functional initiatives across frontend architecture, backend services, observability platforms, and internal developer ecosystems.
At Tesla, I lead AI/Infra org efforts that uphold global ops excellence for AI data centers and Gigafactories through scalable backend services, telemetry systems, monitoring workflows, and internal operational tooling. I led a team of 7 to build an E2E telemetry pipeline and platform tooling, saving $3.5M in annual subscriptions while improving visibility, and I boosted telemetry throughput from 2M to 2.8M pts/sec with a custom tasks scheduler and target allocator in Go.
Previously at LinkedIn and Palo Alto Networks, I built scalable internal platform workflows and observability capabilities—improving SLO visibility across 20+ vertical pillars, increasing error coverage across 5M LOC and reducing MTTR by 83% (60 minutes to 10 minutes), and streamlining deploys with Docker to reduce deployment time by 97%. Earlier at Cisco, I shipped tools and APIs using React, Node.js, Flask, and PHP/Laravel to support internal infrastructure workflows, automation, and data processing, grounded in reliability, performance, and developer experience.
Experience
Work history, roles, and key accomplishments
Led AI/infra backend and telemetry/observability platforms for global AI datacenters and Gigafactories, building end-to-end telemetry pipeline and operational tooling and saving $3.5M in annual subscriptions. Improved telemetry throughput (2M→2.8M pts/sec) and implemented real-time monitoring dashboards and ingestion workflows to reduce alert investigation time by 40%.
Teched lead for Insights and Ops Tooling, building observability, release visibility, and developer productivity platform capabilities for Consumer engineering teams. Delivered a feature catalog for SLO visibility across 20+ pillars, reduced release delays from 10 days to 3 days, and improved web monitoring to reduce MTTR from 60 minutes to 10 minutes.
Worked on Flagship Infrastructure and Productivity to improve productivity for Consumer developers across client and server stacks. Optimized a Kafka pipeline to reduce regression time-to-detection by 98%, built a code review system saving 13k developer hours for 1k+ engineers, and implemented internal tools and APIs using Java, React, GraphQL, and Kafka.
Built audit and compliance services and tooling to help align firewall configurations with industry standards via web-based workflows. Reduced deployment time by 97% and improved availability with Datadog-based monitoring (reducing downtime RCA by 94%), and rewrote a firewall config parser to increase test coverage from 0% to 88% while reducing parsing time by 60%.
Developed internal web tools, automation workflows, and backend services supporting Cisco IT operations and infrastructure tooling. Built APIs and applications using technologies including Flask, Node.js, React, and PHP (Laravel and CodeIgniter), and supported Linux-based engineering automation and Java project tooling.
Education
Degrees, certifications, and relevant coursework
University of California, Davis
Bachelor of Science, Computer Software Engineering
2009 - 2013
Bachelor of Science in Computer Software Engineering at the University of California, Davis (2009–2013).
Availability
Location
United StatesAuthorized to work in
Job categories
Skills
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