Vallab K.

About Vallab K.

I’m an AI-native Full Stack Engineer passionate about building intelligent systems that empower users and scale efficiently. With 4+ years of experience across startups and enterprise platforms, I’ve designed, built, and deployed high-impact features across AI tooling, analytics dashboards, and SaaS infrastructure.My technical journey spans frontend polish, backend design, cloud-native development, and AI/ML infrastructure. At Omneky, I led fullstack development on AI-powered platforms for ad generation and analytics — integrating GenAI workflows, predictive analytics APIs, and scalable creative asset systems. I shipped user-facing tools that reduced post-generation editing time by 40%, built backend infrastructure that accelerated creative iteration across thousands of assets, and led a phased migration from Amplify to a FastAPI-based architecture, improving deployment speed, cold start latency, and developer experience.Previously at Standard AI, I built React + Python tools to support human-in-the-loop ML workflows — saving Ops 60+ minutes per day and streamlining model iteration with intuitive UX. I partnered closely with AI and Data teams to make model outputs more usable: surfacing predictions clearly, visualizing uncertainties, and enabling faster validation and correction.I thrive in ambiguity and excel at turning fuzzy problem spaces into well-architected, scalable systems. Whether I’m designing intuitive frontends or building robust backend services, I bring a fullstack mindset rooted in user impact, performance, and technical clarity. My expertise spans AI-native application development, cloud infrastructure, LLM tooling, and semantic search — anchored by frameworks like FastAPI, React, vector databases, and async workflows. I care deeply about developer experience, system reliability, and building products that translate intelligence into usable, high-leverage tools.Now pursuing my M.Eng in Computer Science at Cornell Tech, I’m expanding my ability to engineer AI systems from the ground up — through hands-on exploration of scalable ML systems, backend resilience, and human-centered AI design. I’m especially focused on bridging the gap between theory and deployment: learning to train and debug models at scale, evaluate algorithms in real-world settings, and build trustworthy, performant AI products. My goal is to create systems that don’t just “work,” but truly work for users — combining clarity, interpretability, and impact.

Experience

1. Co-founder

   Stealth Ai Startup

   Nov 2025 — Present · Manhattan, NY, US

   Building a behavioral intelligence layer for discretionary trading.

Education

• Saint Louis University

  Bachelor of Science - BS, Computer Science

  2017 — 2021

• Cornell University

  Master of Engineering - MEng, Computer Science

• Cornell Tech

  Master of Engineering - MEng, Computer Science