Short bio
Senior AI Engineer with 10+ years of experience designing and deploying production-grade AI systems focused on LLMs, Generative AI, RAG Pipelines, and AI Agent Architectures. Strong expertise in building scalable multi-agent systems, conversational AI platforms, and enterprise AI automation solutions across healthcare, finance, and retail domains. Experienced in Python, PyTorch, Hugging Face Transformers, LangChain, LangGraph, OpenAI APIs, vector databases, and cloud-native AI infrastructure on AWS and Azure. Proven success delivering intelligent systems using prompt engineering, semantic search, embeddings, fine-tuning, tool-calling agents, and modern MLOps practices. Skilled in developing high-performance AI applications leveraging FastAPI, Docker, Kubernetes, MLflow, and scalable microservice architectures for real-time AI inference and workflow orchestration. Passionate about building secure, reliable, and human-centered AI systems that improve operational efficiency and user experiences.
Tech stack
Work experience
- Senior AI Engineer07/2023 - 03/20263 y.
Led the development of intelligent AI Agents and LLM-powered clinical assistants for healthcare decision support, leveraging RAG pipelines, semantic search, and medical knowledge retrieval to improve diagnostic accuracy and reduce operational overhead.
Responsibilities:- Designed and deployed production-grade conversational AI systems integrated with Electronic Health Record (EHR) platforms using GPT-based models, LangChain, and secure API orchestration workflows.
- Built advanced NLP and LLM pipelines capable of processing unstructured medical documents, physician notes, and clinical reports using transformer architectures, embeddings, and vector databases.
- Developed scalable multi-agent workflows for patient risk prediction and intelligent task automation using tool-calling agents, workflow orchestration, and cloud-native AI services.
- Implemented secure AI infrastructure with Docker, Kubernetes, MLflow, and cloud services on AWS and Azure, ensuring scalability, observability, and compliance with healthcare regulations including HIPAA.
- Collaborated closely with data scientists, medical professionals, and platform engineers to deploy reliable and explainable AI systems for real-world clinical environments.
- AI Engineer03/2021 - 06/20232 y.
Developed enterprise-scale LLM-powered virtual assistants and customer support automation systems using RAG, prompt engineering, and semantic retrieval to handle high-volume financial service operations.
Responsibilities:- Built AI document intelligence platforms using transformer-based NLP models, Named Entity Recognition (NER), and vector search for automated financial contract analysis and compliance verification.
- Designed and optimized AI Agent workflows capable of retrieving, summarizing, and analyzing financial data from multiple structured and unstructured sources.
- Applied deep learning, LLMs, and sentiment analysis models to analyze financial news, reports, and market trends, enabling data-driven investment insights.
- Engineered scalable fraud detection systems using machine learning, anomaly detection, and real-time transaction monitoring pipelines.
- Integrated AI services into cloud-native financial platforms using FastAPI, Docker, Kubernetes, and CI/CD pipelines to support highly scalable production environments.
- AI/ML Engineer10/2018 - 02/20212 y.
Developed intelligent recommendation systems and AI-driven personalization platforms using machine learning, NLP, and behavioral analytics to improve customer engagement and conversion rates.
Responsibilities:- Built real-time AI shopping assistants and conversational systems using transformer models, semantic search, and automated recommendation workflows.
- Designed scalable ML pipelines and deployed production AI services using Python, FastAPI, Docker, and cloud-native infrastructure.
- Applied unsupervised learning, customer segmentation, and predictive analytics to optimize marketing campaigns and targeted advertising strategies.
- Developed automated pricing optimization systems leveraging predictive models and real-time analytics for e-commerce platforms.
- Junior AI Engineer08/2015 - 09/20183 y.
Assisted in developing intelligent systems for smart city initiatives using computer vision, machine learning, and AI-based traffic monitoring solutions.
Responsibilities:- Contributed to NLP-driven analytics platforms for extracting actionable insights from large-scale structured and unstructured datasets.
- Developed predictive analytics and forecasting models to support business intelligence and operational optimization initiatives.
- Built data processing and ETL pipelines for scalable machine learning workflows and analytics systems.
- Collaborated with cross-functional teams to customize AI solutions aligned with business requirements and operational goals.
