SPTopen to work

// Full-Stack Engineer · San Jose, CA

Sai Praveen Tatiparthi

I build cloud platforms, production AI systems, and products that ship — currently a founding engineer on a stealth deployment platform, previously AI engineering at Citigroup and Apple.

Selected work

Cloud Deployment Platform
Stealth Startup · Founding Engineer · 2025–present
6M→12Swarm deploy

End-to-end deployment platform on Azure — from git push to live URL in seconds.

  • Cut warm deploy times from ~6 minutes to under 12 seconds with a 5-layer caching architecture and a KEDA-autoscaled warm build-worker pool (13 ms median queue wait, 430 ms cached builds).
  • Built health monitoring with version-aware auto-rollback; clients reconnect to in-flight deploys after page reload via persisted run IDs.
  • Migrated production artifacts to content-addressed storage — 33 deployments, 1,085 files, zero failures.
  • Drove the test suite to 1,900+ tests with enforced CI coverage gates.
TypeScriptNode.jsAzureService BusKEDADockerPostgreSQLReact
Multi-Agent RL for NDN Caching
Master's thesis · SJSU
26.65%vs 22.26% SOTA

Decentralized deep-RL cache coordination that beats a published ICC 2023 baseline.

  • Each network router runs a Double DQN agent (N-step returns, prioritized replay) making caching decisions from local state plus a Bloom-filter neighbor signal.
  • Bloom-filter coordination cuts inter-router overhead ~10x (~250 bytes/update) while raising cache hit rate to 26.65% — beating LRU+LCE (22.60%) and the ICC 2023 multi-agent DQN baseline (22.26%).
  • Built the full NDN simulation stack from scratch (router CS/PIT/FIB, packet model, multi-agent environment), benchmarked from 30 to 500+ nodes with released checkpoints and reproducibility docs.
PythonPyTorchDeep RLBloom filtersGitHub
LLM Job Discovery Pipeline
Personal · in daily use
218→78scored · zero errors

The engine running my own job search — ingests, dedupes, and LLM-scores live postings.

  • Ingests live postings from Greenhouse, Lever, and Ashby APIs across 45 curated companies with content-hash + fuzzy-key deduplication into SQLite.
  • Two-stage matcher: regex hard filters eliminate 64% of postings for free, then batched LLM scoring validates survivors against a structured profile with strict JSON-schema validation and per-batch retry.
  • First live run: 218 postings ingested, 78 scored across 8 LLM batches with zero errors. 109 tests, TDD throughout, offline fixtures for every network/LLM boundary.
PythonSQLiteLLM orchestrationhttpx
Revs Beauty Studio
Client work · live in production
LIVEproduction client site

Production marketing and booking site for a salon in Livermore, CA.

  • 5 routed pages, 25+ reusable components, custom scroll-reveal and parallax hooks.
  • Integrated Vagaro booking and Instagram embeds; iterated over 5 months on performance, accessibility, SEO, and mobile.
ReactTypeScriptViteTailwind CSSNetlifyLiveGitHub

Experience

Full Stack Engineer · Founding Team · Stealth Startup
Feb 2025 — Present
  • Building a cloud deployment platform on Azure end-to-end: deploy pipeline, build infrastructure, LLM services, auth/billing, and the React canvas frontend.
  • Cut warm deploys from ~6 minutes to <12 seconds via 5-layer caching and a KEDA-autoscaled warm builder pool.
  • Shipped LLM orchestration with server-side token metering/billing and LLM-powered build-failure diagnosis with auto-fix.
  • Own fully isolated prod/dev Azure environments (Key Vault, DNS, SSL, App Insights); 1,900+ tests with CI coverage gates.
Full Stack AI Engineer · Citigroup
Mar 2023 — Present
  • AI-driven financial product recommendations (TensorFlow + Angular + Spring Boot) — +30% user engagement.
  • Secure REST APIs serving 1M+ monthly requests at 99.9% uptime under financial-data regulations.
  • Containerized microservices on Docker/Kubernetes (−35% deployment errors); Jenkins + GitHub Actions CI/CD halved deployment cycles.
  • Optimized ML model-serving latency with data science teams — +20% faster real-time credit-risk decisioning.
Software Engineer · Apple Inc
Jul 2021 — Aug 2022
  • Full-stack features for finance web apps (Angular + Spring Boot) — +22% transaction processing speed.
  • Backend microservices for cross-service data synchronization — +28% reliability.
  • PostgreSQL query and indexing optimization — +35% faster response times.
  • Automated regression testing with Selenium + Jenkins — −40% testing time.
Java Full Stack Developer · Hoopers Group
Apr 2020 — Jun 2021
  • Built e-commerce frontend modules (AngularJS) and Spring Boot REST services over MySQL.
  • Optimized API response times by 20% via query design and caching.
  • Reduced production issues by 18% through cross-functional performance and reliability work.

Skills

languages
TypeScript · JavaScript · Python · Java · SQL · C++
frontend
React · Next.js · Angular
backend
Node.js · Express · FastAPI · Spring Boot · Prisma
data
PostgreSQL · MySQL · MongoDB · Redis · Kafka · Elasticsearch
cloud & devops
Azure · AWS · Docker · Kubernetes · GitHub Actions · Jenkins
ai & ml
LLM integration · LLM orchestration · PyTorch · TensorFlow · scikit-learn

Education

M.S. Computer Science · San Jose State University
Expected Fall 2026
B.Tech Computer Science · V.R. Siddhartha Engineering College
2017 — 2021

Certification: AWS Certified Solutions Architect – Associate