Distributed systems / AI infrastructure / identity platforms

Jack Su

I build high-scale systems where product growth, secure identity, ML/AI infrastructure, and practical intelligence features have to work together under real traffic.

GitHub avatar for Jack Su

Senior Software Engineering Leader

Meta / Amazon / Deutsche Bank / Fidelity

Identity: Meta AI, Quest, Ray-Ban smart glasses, SSO, OTP recovery.

Scale: Amazon Photos, distributed data pipelines, high-availability release systems.

AI/ML systems: agentic AI, RAG, ML inference, data pipelines, privacy-first infrastructure.

100M+ users supported across identity and cloud services
100K requests per second peak infrastructure experience
$50B monthly equity volume in trading analytics systems
3 AI competition tracks across Kaggle reasoning and game agents

Work highlights

Systems that scale, recover, and earn trust.

Core signal

A career spent where consumer-scale products, secure identity, and dependable infrastructure all have to move together.

2019 - 2026

Meta

Core developer for Meta AI and wearables identity infrastructure across Meta AI, Quest, and Ray-Ban smart glasses. Improved registration and account recovery flows.

2015 - 2019

Amazon

Built Amazon Photos and Cloud Drive services, distributed data pipelines, facial recognition integration, and release systems with 99.99% availability targets.

2013 - 2015

Deutsche Bank

Modernized global equity trading and analytics systems, including a 10 TB analytics platform integrating 200+ upstream systems.

Earlier

Fidelity, SAS, Aether, S&P

Built high-availability authentication, payroll, workflow, emergency-response, and real-time financial market data systems.

GitHub highlights

Recent public builds and experiments.

Kaggle competition work

Reasoning benchmarks and strategic game agents.

My Kaggle work sits at the edge of efficient reasoning systems: ARC-style visual transformations, minimal neural networks, and game-playing agents that must make strong decisions under simulation constraints.

Resume

Senior engineering leadership with hands-on depth.

The resume covers distributed systems, identity, AI/ML integration, privacy-first engineering, high-volume finance, and cloud platform work across consumer and enterprise environments.

Architecture: microservices, Kubernetes, AWS, agentic AI, RAG, vector DBs.

AI/ML: LLMs, CNNs, predictive analytics, NLP recommendation engines.

Core stack: Java, Python, TypeScript, JavaScript, Spring, performance profiling.

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