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SAIKIRAN KALLURI

Full-Stack Engineer — Frontend · Backend · AI-integrated products

Palakurthi, Jangaon, Telangana – 506252 | +91-8897008268 | kirankalluri888@gmail.com

linkedin.com/in/saikiran-kalluri | github.com/KiranKalluri268 | saikirankalluri.dev

Summary

Full-stack engineer working in React, Next.js, TypeScript, Node and Python. Recently built an internal diagnostics platform at Aude.ai. Outside work I maintain a portfolio codebase with CI-gated unit and browser test suites, and a written record of its own known defects.

Core Skills

Languages: Python, JavaScript, Java

AI/ML: TensorFlow.js, RAG (Retrieval-Augmented Generation), Deep Learning (CNN, ResNet), LangChain

Web/Frameworks: React, Next.js, Node.js, Express, Tailwind CSS

Databases: MongoDB, MySQL, PostgreSQL, Supabase, DynamoDB

Cloud & DevOps: AWS (EC2, S3, Lambda, IAM, IVS, DynamoDB, Amplify), Git, Docker

Other Tools: Linux, Figma, Canva, Tableau, Cloudinary

Internships

Software Engineer Intern – Aude.ai (Jan 2026 – Jul 2026)

  • Worked across the product — a Next.js frontend with a Node and Express backend using Redis — starting with UI bug fixes before taking on larger work.
  • Was given ownership of an internal diagnostics application after the first month, and built it as a Next.js monolith that verifies per-client data integrity for the main product.
  • Designed the dashboard for troubleshooting, with failures visible at a glance, deep-linkable investigations, and a user's-eye UI view paired with its API response.
  • Containerised it with Docker and deployed it on AWS so it reuses the main product's existing single sign-on, with access restricted to authorized members of the engineering team.
  • Proposed and shipped skeleton loading states, now in production.

Forward Deployed Engineer Intern (FDE) – AarogyalinQ Private Limited (Aug 2025 – Jan 2026)

  • Delivered features across four products, working directly with clients to implement them and optimize existing workflows.
  • Built voice input and commands with the ElevenLabs and Bhashini APIs, and containerised and deployed the platform on AWS ECS with GitHub Actions CI/CD and CloudWatch alerting.
  • Worked inside a C++ desktop application to add AWS S3 video storage and AWS IVS live streaming, and built its companion Next.js web application from scratch.
  • Built Axion, a mobile-driven desktop automation system — a Next.js web app, a MERN cloud relay, and a Python desktop agent — controllable by prompt or voice with live step-by-step visibility.
  • Built a remote caregiving platform with WebRTC consultations, Razorpay payments, and an admin dashboard.

Projects

ThirdEyeAI – Real-time Engagement Detection & Meeting Platform (MERN, TensorFlow.js, WebRTC, Python)

  • Engineered a hybrid ensemble bagging model (1D CNN and 1D ResNet) trained on the DAiSEE dataset to achieve 94.25% accuracy in detecting student engagement.
  • Implemented client-side inference using TensorFlow.js, enabling infinite horizontal scaling and ensuring user privacy by processing video streams locally within the browser.
  • Developed a fully functional WebRTC-based meeting engine for online classes, featuring real-time data visualization of engagement metrics for instructors.
  • Integrated a RAG (Retrieval-Augmented Generation) system to allow instructors to query session data using natural language, providing instant insights into student participation and distractions.

CertiSafe – Certificate Management System (MERN, AWS, DynamoDB)

  • Led a 4-member team to build and deploy a certificate management platform for my institute.
  • Integrated AWS DynamoDB and Cloudinary for secure data and media handling; onboarded 95+ users.

Personal Portfolio – Content-Driven Case-Study Platform (Next.js, TypeScript, GSAP, Vitest, Playwright)

  • Content-driven site built from typed JSON, with 229 unit tests and 37 real-browser tests gated in CI alongside lint and type checks.
  • Diagnosed a frame-time regression on iPad by measuring rather than guessing — isolated backdrop-filter across 125 cards as the entire cost, taking frames from 83ms to 16.7ms.
  • Maintain a public status document recording known defects and deferred work, including the limits of my own code.

Education

Bachelor of Technology – Computer Science & Engineering | Vaagdevi College of Engineering | 2022–2026 | CGPA: 8.27

Languages: English, Telugu, Hindi | Strengths: Problem-solving, leadership, curiosity, fast learning