Spearheading development of a benchmarking platform for commercial insurance documents featuring single and batch evaluations, improving response time by 290 seconds from the initial prototype through cProfile diagnostics.

Optimized high-traffic insurance microservices by 41% through async refactoring and API pagination, and implemented secure JWT-based user impersonation to enhance customer support efficiency.

Built Python packages to streamline complex functionalities into a unified developer library.

Implemented end-to-end testing pipelines with Robot Framework and GitHub Actions to strengthen release stability and quality assurance.

Owned an Immunization Dashboard prototype for the CDC Foundation built with MongoDB, Angular, Express.js, and Drone CI/CD, leveraging FHIR standards to give public health teams real-time visibility into immunization data and improve response coordination across IIS networks.

Designed and engineered an LLM benchmarking system powered by Streamlit, FastAPI, and MongoDB, streamlining model & prompt evaluation workflows and accelerating prototyping by 50%.

Promoted to Senior Software Engineer and moved to the Core Services team.

Designed and solely owned the backend for an MVP LLM-powered document copilot built with Flask, LangChain, MongoDB, & Pinecone, powering automation in production environments for 4+ years.

Independently revamped ML workloads using Snowflake UDFs, Procedures, and dbt for server load management, accelerating computations by 27% and reducing query execution time by 55%.

Contributed to backend core services through bug fixes, performance tuning, and feature development to support continuous product improvements and scalability.

Recognized with the Emerging Player Award in the Data Science & Engineering vertical.

Led backend development for a large-scale Risk Analysis system using Flask, PostgreSQL, MongoDB, and RabbitMQ supporting over 100K concurrent users.

Supported CI/CD pipelines and cloud infrastructure management using Azure DevOps and Kubernetes, ensuring smooth deployments and scalable operations.

Part of a two-member Orchestration team responsible for building and maintaining Apache Airflow pipelines to automate and monitor ETL, ML and analytics workflows.