AI Agent Engineer with 4 years building autonomous agentic systems at enterprise scale. At ServiceNow, designed and owned a LangGraph multi-agent system that retrieves, reasons, and acts across enterprise data, resolving thousands of support cases monthly without human handoff. Proven across the full agent lifecycle from workflow design and RAG grounding through prompt guardrails, eval loops, and production deployment. The cross-system grounding architecture built at ServiceNow transfers directly to enterprise finance automation including account reconciliation, variance analysis, and month-end close on platforms like SAP and NetSuite
🤖 Agentic AI & LLM Engineering
🔍 RAG & Vector Databases
🧮 Machine Learning & Deep Learning
🔧 MLOps & Infrastructure
☁️ Cloud & Big Data
💾 Databases
LangChain | RAG | FastAPI | Neo4j | PyTorch
Production-grade RAG system for medical document intelligence:
- 🧠 Architected RAG pipeline converting multimodal medical documents into structured entities with 89% accuracy
- 📊 Built Neo4j knowledge graph vectorizing 15K+ medical concepts for semantic search
- ⚡ Deployed containerized FastAPI system handling 100+ concurrent requests
- 🔍 Implemented hybrid retrieval combining vector similarity and graph traversal
PyTorch FSDP | Flash Attention | ONNX | Quantization
Optimized ML training and inference infrastructure:
- 🚀 Built distributed training system achieving 90% GPU efficiency on dual-GPU setup
- ⚡ Boosted training speed 1.7× processing 158K multimodal samples using Flash Attention
- 📉 Reduced memory consumption by 16% through efficient attention mechanisms
- 🎯 Maximized inference achieving 5× throughput using ONNX export and INT8 quantization
XGBoost | Kafka | Spark | Kubernetes | MLOps
Real-time fraud detection system with complete MLOps pipeline:
- 🎯 Achieved 99.6% accuracy with XGBoost model using SMOTE for class imbalance
- 🔄 Built real-time processing pipeline using Kafka & Spark for streaming data
- 🚢 Implemented end-to-end MLOps with GitHub Actions, Argo CD & GKE
- ⏱️ Optimized for <100ms inference latency at 100K+ TPS scale
Kubernetes | Docker | Jenkins | GitOps
Production MLOps platform for streamlined model deployment:
- 📦 Containerized ML applications with Docker & Kubernetes orchestration
- 🔄 Automated CI/CD pipelines via Jenkins & GitHub Webhooks
- 🚀 GitOps-based deployments with version control & automated rollbacks
- 📊 Optimized data preprocessing reducing runtime by 66%
Northeastern University - Boston, MA
Master of Science in Information Systems (Big Data & AI/ML Engineering)
Anurag University - Hyderabad, India
Bachelor of Technology in Electrical Engineering
- 🎖️ Oracle Cloud Infrastructure 2025 Certified Generative AI Professional
- 💻 Open Source Contributor: Ivy ML Framework - 20+ merged PRs optimizing matrix operations
- 🌟 Building autonomous AI systems that process millions of transactions monthly
