Designed, developed, and deployed high-performance Python applications and microservices/APIs for Data & AI/Agentic platforms. Collaborated with data engineers, scientists, and AI engineers to productionize sophisticated intelligent agent workflows and applications. Implemented robust data validation and serialization with Pydantic, ensuring system-wide data integrity and consistency. Built and maintained FastAPI-based REST APIs, achieving low-latency, high-throughput service performance. Containerized services with Docker and orchestrated deployments for consistent development, test, and production environments. Integrated structured logging and monitoring solutions to improve observability and reduce troubleshooting time. Developed secure and efficient database interaction layers with SQLAlchemy ORM, managing schema evolution and persistence. Contributed to architectural design discussions, code reviews, documentation, and Python development best practices. Delivered team demos, pres

Software Engineer at Invesco

September 1, 2018 - October 1, 2022

Full-stack development of portfolio analysis tools using Angular, Java (Spring Boot), and PostgreSQL. Built AI-powered services for risk modeling and recommendations using Python, PyTorch, and Scikit-learn. Developed modular UI components in React and Angular; built backend APIs using Node.js (Express) and Java Spring Boot with PostgreSQL and MongoDB. Created infrastructure automation with Terraform to deploy AWS-hosted applications, and integrated graph queries with Neo4j/Cypher. Managed Docker containers for microservices and implemented CI/CD pipelines. Developed ETL processes using AWS Glue and integrated ML APIs into client platforms. Containerized with Docker and deployed on Kubernetes with Helm. Automated model training, deployment, and versioning using MLflow and AWS Step Functions. Worked with DynamoDB and MongoDB for high-performance data management. Participated in code reviews, architecture discussions, and knowledge sharing to boost team productivity.