Specializing in Generative AI, MLOps, and Data Engineering. Building autonomous systems that reason, scale, and solve complex real-world problems.
AI Research Engineer specializing in Agentic Orchestration and High-Throughput MLOps. I build autonomous systems that bridge the gap between lab research and production revenue. Most recently, I engineered Project NEXUS, a swarm of 15+ concurrent voice agents utilizing Redis-backed state machines for 100% execution integrity. At Stellis Labs, I architected a Contrastive Search Module using fine-tuned Llama-3 and hybrid embeddings, reducing inference latency by 40%. With a background in Data Engineering building data pipelines to vectorized SQL layers for Fortune 500 clients at Cognizant. I build the robust, fault-tolerant infrastructure required to move GenAI from a "chat demo" to an enterprise asset.
Multi-Agent Voice Swarm & Coordination Engine (AI Voice Agent)
Architected a "Multi-Agent Voice Swarm" capable of initiating 15+ independent ElevenLabs voice agents simultaneously to handle complex coordination tasks. Integrated an Admin Analytics dashboard for cost tracking, live call intervention, and automated calendar synchronization.
Generative AI Motion Correction Tool
Developed a physiotherapy assistance tool improving movement correction accuracy by 30% using Procrustes analysis and DTW. Integrated AI recommendations with Cortex Mistral 7B and Snowflake, boosting adherence by 25%.
Production MLOps Architecture
Deployed production MLOps ecosystem on Google Cloud using Docker and Airflow. Created hybrid retrieval engine with custom LLM Agent to autonomously sanitize and analyze high-volume unstructured social data streams.
Advanced RAG Architecture
Built hybrid embedding framework leveraging mxbai-embed-large and fine-tuned LLaMA 3 model for semantic opposition detection. Implemented multi-vector indexing with ChromaDB for efficient retrieval.
Adversarial Safety Research
Analyzed vulnerabilities in Multi-Agent Systems by mathematically modeling adversarial attacks. Investigated cascading failures and proposed System Role-Based Filters to mitigate risk.
LLM-Based Hardware Optimization
Developed LLM-based autotuning system using GPT-4 to optimize hardware and software parameters, enhancing HPC resource utilization by 30%.
Humanitarians AI & Bear Brown Company
January 2025 - May 2025
Northeastern University
December 2024 - June 2025
Cognizant Technology Solutions
August 2022 - July 2023
Cognizant (Generative AI Research Lab)
March 2021 - August 2022
Bennett University
May 2020 - June 2020
Northeastern University
August 2023 - December 2025 | GPA: 3.8/4.0
Coursework: Machine Learning Operations (MLOps), Gen AI with LLM in Data Engineering, LLM-based Dialogue Agents, Natural Language Processing, Data Mining, Cloud Computing
VNR VJIET
2017 - 2021
Coursework: Artificial Intelligence & Neural Networks, Data Structures & Algorithms, Computer Graphics, IoT, Cognitive Science, Cyber Security
Patent Application Num: 202141054101, December 2022
Designed a hardware-integrated Computer Vision system for real-time monitoring. Optimized inference latency for low-compute devices (Raspberry Pi) using lightweight CNN architectures.
International Journal of Engineering Research & Technology (IJERT)
Developed a security framework analyzing lattice-based cryptographic resilience against quantum computing attacks. Modeled decryption vectors to harden digital infrastructure.
IEEE 7th International Conference for Convergence in Technology (I2CT), 2022
Developed a computer vision system for COVID-19 detection achieving 96% accuracy using deep learning models.
Annual Technical Symposium, India, September 2021
Presented research on brain-computer interface technologies and applications.
Whether you're looking to optimize your ETL workflows or architect a new Multi-Agent system, I'm always open to discussing complex engineering challenges.