AI Engineer • Full-Stack Developer
Bhoompally Kalyan Reddy
I'm a
PDF preview isn't supported on this device. Download to view the full resume.
Download Resume
I am a 3rd-year Computer Science and Engineering student at ACE Engineering College (JNTUH), Hyderabad, and the Founder of AuraCore AI — a multi-agent orchestration platform processing 100+ daily queries with 98% uptime. I specialize in building production-grade AI systems using Python, FastAPI, CrewAI, and Retrieval-Augmented Generation (RAG), as well as responsive full-stack web applications using React.js, Next.js, and Node.js.
I am a published researcher in IJARSCT (DOI: 10.48175/IJARSCT-32733) and have deployed 30+ products with 14 professional certifications. I am passionate about autonomous agentic workflows, offline LLM inference, and building innovative software solutions that create meaningful impact.
Bachelor of Technology in Computer Science Engineering
Intermediate (MPC)
SSC
AuraCore AI Command Center
Spearheaded the architecture of a multi-agent platform processing 100+ daily queries with 98% uptime. Optimized a high-performance RAG system, reducing retrieval latency by 45% across 500+ documents. Orchestrated three specialized AI agents using CrewAI to deliver 60% faster task completion.
GSSoC'26 (GirlScript Summer of Code)
Actively contributing to open-source projects under the prestigious GSSoC program, currently holding a prestigious Rank #103 on the national leaderboard. Developing features for the AI Code Reviewer repository, integrating advanced LLM capabilities to automate code analysis, detect vulnerabilities, and improve developer workflows.
NSoC'26 (Nexus Summer of Code)
Successfully completed the NSoC'26 program, achieving a prestigious Rank #54 on the national leaderboard. Served as the Project Maintainer for the Lexicon repository, managing 794+ commits, 52 pull requests, and 7 contributor forks. Integrated Groq AI backend with Llama 3.3 and deployed 60+ production builds on Vercel.
InAmigos Foundation
Completed a professional software development internship, collaborating with engineering teams to build and optimize robust applications. Focused on writing clean, maintainable code, debugging complex issues, and participating in agile development workflows to deliver high-quality software solutions.
IJARSCT International Journal
Co-authored peer-reviewed research paper "Sarathi: Smart Emergency Navigation System" (DOI: 10.48175/IJARSCT-32733), reducing emergency response times by 30% through intelligent routing algorithms with 0.5-meter proximity accuracy using real-time GPS coordinates.
ACE Engineering College / OutSkill / KL University
Ranked Top 4 out of 200+ in Code Sprint 2026. Ranked Top 7 in KL University Hackathon. Completed AWS cloud deployment bootcamp and Generative AI masterclass with OutSkill.
Tracing my journey through the models, tools, and agents that define my engineering path.
Where it all began — first exposure to prompt engineering, conversational AI, and understanding how large language models reshape human-computer interaction.
Harnessing Google's multi-modal reasoning engine — text, image, audio, and video understanding in a single unified model. Deep API integration for production apps.
Explored unfiltered, real-time AI insights via Elon Musk's xAI ecosystem — live data streams, zero-censorship responses, and raw analytical power.
High-efficiency open-weight models specializing in code generation, mathematical reasoning, and cost-effective inference at scale.
Advanced prototyping, prompt engineering, API management, and fine-tuning experiments — turning raw model capabilities into production-grade applications.
Bridging the gap between creative UI design and functional engineering — using AI to generate, iterate, and ship interfaces at unprecedented speed.
Exploring 128K+ token context windows, state-of-the-art Chinese open-source LLMs, and multilingual reasoning capabilities for global-scale applications.
Lightweight, high-performance models for edge computing and local deployment — running AI entirely on-device without cloud dependency.
Mastering the most sophisticated reasoning and coding agent — complex architectural builds, multi-file refactoring, and production-grade software engineering.
The IDEs, agents, and platforms that translate AI intelligence into shipped products.
The bedrock of modern software development — fully customized with extensions, keybindings, and integrated terminal workflows for maximum velocity.
First encounter with truly symbiotic AI coding — codebase-aware completions, multi-file edits, and conversational debugging that 10x developer speed.
Exploring complex agentic workflows — multi-step autonomous reasoning, tool-use orchestration, and self-correcting systems that think before they act.
Pushing the absolute limits of AI-assisted engineering — advanced generative agents, full-stack autonomous builds, and the future of software creation.
Evolving the developer experience with autonomous AI IDE integration, empowering massive scale full-stack architecture generation and seamless workflows.
Architecting self-learning frameworks and highly scalable backend solutions that orchestrate multiple AI agents in real-time server environments.
Research project (IJARSCT 2026) for a smart emergency location sharing and intelligent routing system using real-time GPS integration.
A versatile Android-based AI agent repository for automated system interaction, task conductor logic, and mobile automation.
Advanced system security and verification framework utilizing AI-integrated threat analysis for secure digital environments.
High-performance pipeline for automated cleaning, processing, and transformation of large-scale AI datasets and LLM training data.
AI-powered presentation engine designed for immersive 3D visual storytelling and dynamic slide deck generation.
Generative media platform focused on high-fidelity AI avatar creation and real-time vision processing (Veo Vision Engine).
A conversational AI agent specialized in natural language interaction, emotional intelligence, and user companionship.
Robust, cross-platform Point of Sale application built with Flutter, featuring offline-first persistence and license management.
Secured Top 4 position in a competitive 24-hour hackathon among 200+ participants.
Ranked in the top 7 at KL University's inter-college technology hackathon.
Participant in India's premier open source hackathon, contributing to open source ecosystems.
Presented a working project demo to faculty and industry experts at KLH University (result awaited).
A multilingual voice/text translator with AI capabilities.
A responsive e-commerce website for Deccan Fresh, featuring product listings, cart functionality, and user authentication.
A QR code generator with customizable options and real-time preview.
A local-first multilingual voice & text AI assistant supporting English, Hindi & Telugu. Features Ollama LLM runtime, Vosk STT, Piper TTS, adaptive tutoring, and world-knowledge grounding.
A browser-based AI avatar studio with realistic phoneme-driven lip sync, emotion-aware expressions, multi-band audio analysis, and one-click video export in WebM/MP4. Supports YouTube upload flow.
A 100% browser-based AI document processing platform with 10 tools: PDF compress/merge/split, image compression, OCR (13 languages), AI summarizer, keyword extractor, question & bullet generator. No server needed.
A cross-platform mobile app that converts any topic into an educational video — script generation, TTS narration, AI image generation, and FFmpeg rendering. Supports English, Telugu & Hindi. Built with React Native + Expo.
A full-featured cross-platform Point of Sale application built with Flutter. Supports product catalogue, order management, billing & receipt generation, and multiple payment methods (Cash, Card, UPI). Runs on Android, iOS & Web.
A CNN-based deep learning model trained on 10,000+ food images that analyzes food items via camera or upload and returns detailed nutritional data including calories, macronutrients, and health recommendations. Achieves 92% accuracy.
An AI-driven cybersecurity detection framework that classifies network traffic as benign or malicious using ensemble ML models (Random Forest, XGBoost, SVM). Achieves 95% precision in detecting threats, tested against 50+ threat vectors.
