I am an AI/ML and cloud engineer focused on building secure, production-minded GenAI systems. My work spans retrieval-augmented generation, LLM security, adversarial machine learning, cloud observability, and event-driven security platforms.

At SUNY Polytechnic Institute, I work on applied AI research involving RAG, secure inference, deep learning, and adversarial robustness for cybersecurity-focused applications. I enjoy taking ideas from architecture to a working system: APIs, retrieval pipelines, model integration, evaluation, containerization, observability, and security controls.

Current interests: secure enterprise AI, agentic workflows on the Model Context Protocol (MCP), AI red teaming, LLM evaluation, cybersecurity automation, and scalable MLOps.

A self-hostable agent platform that securely connects employees to internal knowledge, code, email, calendar, and operational tools — built on the Model Context Protocol (MCP).

• Built a FastAPI gateway with JWT authentication, RBAC, bcrypt password hashing, password-strength policy, rate limiting, token revocation, and a full audit log.
• Implemented a planner-driven agent loop with retry, structured tool traces, human-approval gating on destructive actions, and a provider-agnostic LLM layer (Anthropic and OpenAI).
• Shipped 18 MCP tools across 7 connectors: GitHub, Gmail, Calendar, sandboxed File System, read-only PostgreSQL, RAG knowledge base, and system tools.
• Added RAG over Markdown and PDF docs with heading-aware chunking, citations, and Chroma or PGVector backends.
• Built a Next.js 14 frontend (login, chat with tool-call viewer, document upload, settings) and one-click Codespaces support for cloud demos.
• Hardened with HSTS, CSP, X-Frame-Options, CodeQL SAST, Dependabot, 16 security regression tests, and a published SECURITY.md threat model.
• Containerized for Docker Compose and Kubernetes with Prometheus metrics and structured logging.

Python FastAPI Next.js MCP JWT RBAC RAG Chroma PGVector Anthropic OpenAI Docker Kubernetes Prometheus CodeQL

A local-first RAG assistant for investigating cybersecurity logs and reports.

• Built a FastAPI and Streamlit application with JWT-protected upload and chat workflows.
• Supports PDF, TXT, and LOG ingestion, recursive chunking, per-user FAISS indexes, and grounded answers with source citations.
• Includes Ollama, OpenAI, and Claude provider options, prompt-injection detection, SHA-256 file metadata, and SQLite audit logging.
• Added Docker Compose, automated tests, GitHub Actions, CodeQL, Dependabot, secret-scanning guidance, and an MIT license.

Python FastAPI Streamlit LangChain FAISS Ollama OpenAI Claude Docker

An event-driven security and CloudOps platform for log ingestion, streaming, detection, and alert persistence.

• Designed a decoupled pipeline using FastAPI, Redpanda/Kafka, detection services, and PostgreSQL.
• Implemented normalized event ingestion, streaming detection, scored alerts, and end-to-end local validation.
• Documented a roadmap for contextual retrieval, agentic reasoning, automated remediation, observability, and secure cloud deployment.

Python FastAPI Redpanda Kafka PostgreSQL Docker

A computer-vision interface that uses hand landmarks and gesture recognition for real-time cursor control.

Python OpenCV MediaPipe Computer Vision

Mission Control

Build Dashboard

Pac-Man Contribution Run

Activity Radar

GenAI Engineer, SUNY Polytechnic Institute

January 2026 - Present

• Developing applied AI systems for contextual retrieval, summarization, and grounded question answering using LangChain, LlamaIndex, FastAPI, and PostgreSQL/PGVector.
• Building reproducible ML and deep-learning workflows for secure AI and cybersecurity research.

GenAI Systems Research Engineer, SUNY Polytechnic Institute

July 2025 - December 2025

• Built a secure offline LLM platform for privacy-sensitive environments using OpenWebUI, RAG, FastAPI, and local model serving.
• Evaluated prompt injection, jailbreak, and red-team attacks and contributed to secure API, network, encryption, and containerization strategies.

Data and Cloud Engineer, ConnX AI

April 2023 - July 2023

• Automated cloud observability and operational diagnostics using Python, Prometheus, Grafana, Nagios, Zabbix, and AWS CloudWatch.
• Developed real-time log analytics, anomaly detection, IP reputation, routing diagnostics, and containerized CI/CD workflows.

• Video and Audio Deepfake Datasets and Open Issues in Deepfake Technology
  • Forensic Sciences, 2024
• Design and Implementation of an AI Virtual Mouse Using Hand Gesture Recognition
  • Volume 14, Number 1, March 2024
• An Intelligent Way to Recognize Digits Using Convolutional Neural Networks
• Scarlett: Virtual Assistant and Browlett Browser
• Tachyon: Bike Rentals Made Easy

My deepfake-audio research included a survey of more than 30 studies covering datasets, detection methods, and open challenges in forensic AI.

• M.S., Network and Computer Security - SUNY Polytechnic Institute
• B.E., Computer Science - Methodist Engineering College
• CompTIA Security+ (SY0-701)
• AWS Academy Cloud Foundations
• Google Cloud Ready Facilitator
• Cisco DevNet, Cybersecurity, and Networking Essentials

I am interested in engineering roles where AI quality, security, and systems design matter together. I am especially excited by work involving enterprise RAG, AI agents, model evaluation, AI security, cybersecurity automation, and cloud-native ML platforms.

For collaboration or opportunities, reach me at saivirinchi103@gmail.com or connect on LinkedIn.