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San Francisco, CA · Verified Portfolio
Alex Rivera

Staff AI Systems Engineer

Staff AI Systems Engineer with 8+ years building distributed execution engines, high-dimensional vector search pipelines, and developer tooling. Previously scaled core infrastructure at scale-ups from 0 to 10M+ daily active requests with sub-second latency.

100M+
Daily Agent Steps
<25ms
Vector Query Latency
8+ Yrs
Years Experience
4.8k★
Open Source Stars

Featured Projects & Case Studies

Synthesized from repository analysis and CV technical highlights.

Autonomous Agent Execution Runtime

Engineered a multi-tenant agent execution pipeline processing 100M+ steps daily with sub-second feedback loops and isolated memory sandboxes.

RustWebAssemblyTypeScriptNext.js 16
100M+ daily agent stepsView Code ↗

Distributed Vector Search Engine

High-throughput indexing pipeline integrating high-dimensional vector embeddings with relational graph queries and sub-25ms latency.

PythonPyTorchQdrantRust Core
1.2B vectors queried in <25msView Code ↗

Real-time Edge Analytics Platform

Edge-native analytics platform supporting real-time streaming queries, multi-region caching, and zero cold starts.

React 19TurbopackServer ActionsRedis
Sub-10ms edge cache resolutionView Code ↗

Design System & Component Engine

Enterprise design tokens architecture and headless component system adopted by 40+ engineers across 12 product squads.

TypeScriptTailwind CSSFigma APIRadix
10x component adoption velocityView Code ↗

Work Experience

Career trajectory and technical impact milestones.

Staff Infrastructure & AI Engineer · Aether AI Platforms

2023 — Present · San Francisco, CA
  • Led architecture for multi-tenant agent runtime processing 100M+ daily steps with 99.999% uptime.
  • Engineered custom Rust WebAssembly sandboxes reducing cold-start compute latency by 72%.
  • Mentored a distributed team of 14 engineers across systems and platform squads.

Senior Distributed Systems Engineer · Nexus Data Labs

2020 — 2023 · Remote / New York
  • Designed vector embedding search cluster querying 1.2B high-dimensional embeddings with <25ms p99.
  • Migrated monolithic analytics backend to event-driven Kafka and Redis stream pipelines.

Technical Skills & Core Tooling

Categorized technologies extracted from hands-on production experience.

Languages & Runtimes
RustTypeScriptPythonGoWebAssemblyNode.js
Frameworks & UI
Next.js 16React 19TurbopackTailwind CSSGraphQL
AI & Distributed Systems
PyTorchVector EmbeddingsQdrantRedisKafkaDockerKubernetes
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