Full-stack AI EngineerSai Rohit Sanniboyina
Founding engineer. I build, scale, and maintain apps end to end. Pixel-perfect frontends, production-grade backends, and the LLM systems that power them, from agentic workflows to AI features in production.
One engineer, the whole stack.
Pixel-perfect frontends
Interfaces that match the design to the pixel and stay fast under load.
Production backends
APIs, data models, and services built to be reliable, observable, and secure.
Scale & infrastructure
Infra, pipelines, and architecture that grow from prototype to millions.
AI & LLM systems
Agentic workflows and LLM features wired into real products: retrieval, tool use, and evals, not demos.
Where I’ve built.
Founding Software Engineer
De-facto founding engineer of an AI landing-page personalization product, owning architecture across frontend, backend, analytics, AI workflows, and infrastructure from pre-launch to first paying customers.
Frontend Developer
Built production marketing and product sites for clients on Next.js with headless CMS (Contentful, Payload) and GraphQL, focused on motion, responsiveness, and performance.
Frontend Developer · Intern
Shipped client-facing web interfaces remotely, translating designs into fast, accessible, pixel-accurate React frontends.
R&D Member
Led peer workshops on web fundamentals (HTML, CSS, semantic markup, and how browsers render) plus an intro Python project.
Tools I reach for.
How I build.
Align first.
Before I write code, I talk the problem through with the team and map every edge case, however unlikely, so the corners are handled up front instead of surfacing as bugs later. Getting the problem statement right is half the work, and it's the half that's cheapest to fix on a whiteboard rather than in production.
Communicate.
I keep the team and management in the loop with where things stand and what's blocking them, and I adapt to however a team already works. Waterfall or agile, I fit the process that's in place rather than imposing my own. Most engineering problems are really communication problems wearing a costume.
Debuggable by default.
Observability is part of building the feature, not a thing I bolt on after an incident. Logs, traces, and metrics go in as I build, so when something does break, the answer to why is already there and a fix takes minutes instead of a day of guessing.
Keep it simple.
I write code my teammates can read, not just me, and I reach for the right tool for the job instead of overcomplicating things before they need it. When a flow gets involved, I document it with a diagram so the team can grasp the system at a glance rather than wading through code and docs to reconstruct it.
Projects I’ve shipped.
WYSIWYG Editor
→Replaced a canvas-masked screenshot editor that round-tripped every change through a web scraper with a live iframe editor backed by a published Chrome extension.
Web Scraper
→A browser automation service core to Optimeleon's AI product. I led moving its element and CTA detection off AI and onto pure code, cutting response time from over 5 minutes to under 30 seconds.
5.0 on Upwork.
“This job had to be done fast and Sai did it faster than I anticipated. He was responsive, communicative and attentive to the details.”
“Good knowledge for pixel-perfect conversions. Thank you!”
“It was a pleasure working with Sai.”