I'm passionate about building and shipping AI software systems that solve real-world problems. With over 4+ years of experience in AI/ML engineering, I have experience in Conversational AI, Large Language Models (LLMs), and Multi-Agent Systems.
My focus is on building intelligent systems to change the way we communicate with computers and create more personalized AI experiences that adapt to individual users and business needs.
- Build end-to-end conversational AI systems with multi-agent architectures
- Design and implement RAG pipelines for enterprise knowledge management
- Explore prompt engineering and context engineering for optimal LLM performance
- Develop voice AI applications with speech-to-text and text-to-speech integration
- Create scalable AI solutions from prototype to production deployment
The Challenge: In a 4-hour sprint, our team tackled a real sales pain point — companies receive tons of inbound calls daily, with sales reps wasting valuable time reviewing call transcripts in CRMs, often spending ~5 minutes per contact just to figure out if a lead is worth pursuing.
Our Solution: Built an AI-powered sales-call filtering system (cheekily named "Legit or Sh*t" by the team 😅) that automates the entire lead qualification process using a two-layer AI system that transcribes calls, adds real-time company context, and intelligently classifies them as potential leads, spam, or uncertain.
Technical Implementation:
- Workflow 1 (Automatic): Triggered in real-time during live calls, instantly labeling leads before they enter the CRM system
- Workflow 2 (Manual): CRM-integrated batch processing to label and filter existing contacts at scale
Impact: Sales teams can save 1000+ hours annually and cut operational costs by ~50% by filtering out low-value calls before they reach the CRM.
🏆 Outcome: Won the hackathon for innovative approach, rapid execution, and demonstrable business value in just 4 hours!
Oprina - Conversational AI Avatar Assistant
Built a revolutionary voice-powered AI assistant combining conversational intelligence with interactive avatar technology. The platform transforms email management, calendar scheduling, and productivity tasks into natural voice conversations.
🏗️ Architecture: 5-component microservices (Frontend, Backend, AI Agents, Database, External APIs) with specialized Email and Calendar agents powered by Google's Agent Development Kit and deployed on Vertex AI.
🛠️ Tech Stack: Google ADK, Vertex AI, React 18 + TypeScript, FastAPI + Python, Supabase, Google Cloud Run, HeyGen Streaming Avatars, Gmail & Calendar APIs, Speech-to-Text & Text-to-Speech
🎯 Outcome: Didn't win, but gained incredible experience building and deploying a complete platform in under a month!
🔗 Links: Live Demo | GitHub Repository
A production-ready RAG system that synthesizes academic content using multi-retriever setups, LLM-based document evaluation, and smart query rewriting with web search integration.
Tech: LangChain, LlamaIndex, Faiss, OpenAI, PostgreSQL
Fine-tuned a Mistral 7B Instruct model with QLoRA for high-quality English–Telugu translation using a 140k sentence-pair dataset.
Tech: PyTorch, Transformers, Hugging Face, QLoRA
A Python package developed at William & Mary for validating and reviewing geoBoundaries shapefiles. Published on PyPI and integrated into open-source workflows.
Tech: Python, Prefect, Web Scraping, Dataverse API
- Published open-source tools like
pygeoboundaries - Mentored undergraduates in AI and ML applications at Texas A&M University
I’m always open to collaboration in Generative AI, agentic systems, or cutting-edge RAG applications.
- LinkedIn: LinkedIn Profile
- Hugging Face: Hugging Face Profile
- Email: [email protected]