AI Software Engineer with 2+ years of experience building and deploying production-grade AI systems across Generative AI, Large Language Models (LLMs), machine learning, and python Developement. I specialize in turning cutting-edge research into scalable, business-ready solutions that drive automation, efficiency, and measurable ROI.
My work spans GenAI and LLM applications including RAG systems, prompt engineering, fine-tuning (LoRA/PEFT), vector databases, and agentic workflows, as well as traditional ML across NLP, computer vision, and predictive modeling. I have hands-on experience designing end-to-end systems - from data ingestion and feature engineering to model deployment, monitoring, and CI/CD-enabled MLOps.
Technically, I work extensively with Python, SQL, PyTorch, TensorFlow, and modern AI stacks such as LangChain, Hugging Face, OpenAI APIs, and FastAPI. On the infrastructure side, I’ve deployed solutions using Docker, Kubernetes, MLflow, and cloud platforms including AWS, Azure, and GCP, while supporting data pipelines with Spark, Kafka, and Snowflake.
I’m currently focused on Generative AI, LLM-powered applications, and applied ML engineering roles where I can build impactful, real-world AI products.
Always open to connecting with fellow engineers and industry professionals to explore opportunities and work on forward-thinking engineering challenges.