I am an AI Engineer with hands-on experience building production-oriented multi-agent systems, LLM pipelines, and retrieval-augmented generation architectures. I work across the full machine learning lifecycle, from data collection and annotation through model training, deployment, monitoring, and optimization.
I have developed AI solutions for healthcare, browser automation, analytics, and computer vision. My work includes agent orchestration, intent routing, semantic search, structured outputs, hallucination detection, and context-window and token-cost optimization.
I am proficient in Python, SQL, and modern web technologies, with practical backend experience using FastAPI, Flask, and Django. I also build AI-enabled user experiences using React and integrate APIs, databases, vector stores, and cloud infrastructure into reliable systems.
My machine learning background covers deep learning, NLP, classification, named entity recognition, predictive analytics, object detection, and model evaluation. I have used frameworks including PyTorch, TensorFlow, Keras, and scikit-learn to deliver practical data-driven solutions.
I am experienced with cloud and DevOps workflows across Azure, AWS, and GCP, including Docker, Kubernetes, CI/CD, GitHub Actions, and Azure Pipelines. I am a collaborative, analytical, and self-motivated learner focused on applying advanced AI to real-world problems.
