AI Engineer

Built an agentic IT audit platform featuring a RAG-based chatbot and an automated document-analysis pipeline supporting audit planning, execution, and reporting.

Benchmarked Snowflake, Nomic, and Qudo embedding models for retrieval accuracy and latency. Rebuilt document extraction from regex-based matching to a structure-first parser, and resolved GPU memory and concurrency issues in a Dockerized FastAPI, LLM, and vLLM stack.

Led the retrieval-layer migration from Qdrant to PostgreSQL with pgvector to improve the platform's data and retrieval architecture.

Built intelligent FastAPI microservices with structured API request and response handling. Integrated OpenAI and LangChain to create natural-language product search pipelines.

Evaluated MongoDB, SQLite, and PostgreSQL with pgvector for use-case-specific storage needs. Developed and tested FastAPI services with Postman and implemented real-time computer vision detection and recognition features using deep learning models.

Developed deep learning image-classification solutions using Python, PyTorch, NumPy, and Pandas for data processing and analysis.

Applied transfer learning with pre-trained EfficientNet and MobileNet models, fine-tuning them for classification tasks. Designed and trained convolutional neural networks using MNIST and Fashion MNIST image datasets.

Bachelor's degree program in Computer Science with a specialization in Artificial Intelligence.

Completed the National Freelancing Training Program certification.