I design and build high-throughput, low-latency distributed systems, serverless data pipelines, and production ML integrations. My work focuses on scalable APIs, operational excellence, and data-driven systems for advertising and analytics.
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Experience
At Amazon Advertising, I develop scalable backend services and high-throughput data pipelines using AWS technologies including ECS, Lambda, DynamoDB, Step Functions, Glue, and Athena. I built robust ad labeling systems that support both pre- and post-bid filtering to improve ad relevancy, while separately enhancing brand safety systems to protect advertisers and ensure compliance. My work enabled efficient large-scale processing and evaluation of ad data, significantly boosting overall ad quality.
Leveraging agent-driven AI and model-driven control logic (MCP), I developed a validation framework to evaluate ad labels against centralized metadata, schemas, and semantic constraints, preventing invalid or inconsistent labels from propagating downstream. Additionally, I prototyped a Slack-integrated RAG chatbot using Amazon Kendra and AWS Bedrock to accelerate onboarding, improve ticket tracking, and provide leadership with real-time system visibility. I also led seamless service transitions and implemented automation to improve operational reliability and customer onboarding.
Tech Stack: AWS (Lambda, EC2, Fargate, Batch Jobs, RDS, SNS, SQS, Step Functions, DynamoDB, Bedrock, Kendra, CloudWatch, Glue, Athena, ElastiCache, S3), Distributed Systems, Apache Iceberg, GraphQL, Kafka, Serverless Architecture, Machine Learning, CI/CD, Observability, Java, Python, TypeScript
Developed API integrations with Google Calendar and built ETL pipelines with data preprocessing for PostgreSQL database ingestion and optimization.
Tech Stack: Python, REST APIs, PostgreSQL, ETL Pipelines
Mentored students in Information Retrieval, Computer Security, Discrete Structures, and Numerical Computations courses. Researched fake news detection using machine learning and NLP at AI-SSGL lab. Developed automation scripts for grading and maintained research lab website.
Tech Stack: Python, Machine Learning, NLP, WordPress, Automation
Revamped ML test suites and built preprocessing tooling to accelerate NLP and unsupervised workflows, reducing runtime and manual effort. Created PyQt utilities for automated data preparation and visualization and prototyped ML solutions to improve software testing and evaluation.
Tech Stack: Python, Keras, PyQt, Machine Learning, NLP, Data Visualization, Test Automation
Education
Key Projects
Built a full-stack diabetes prediction app using a Random Forest model with Google Maps and Twilio for real-time alerts. Dockerized and deployed on AWS EC2 with PostgreSQL.
Developed an Android app (Java) for a football fantasy tournament and a Flask REST API + scraper to provide live data and scoring.
Architected a P2P distributed system with replication and version control to enable resilient file CRUD operations across nodes.
Technical Skills
Distributed systems design, high-throughput data pipelines, serverless architecture, API development and modeling, ML/AI integration, infrastructure and performance optimization, real-time event-driven systems, and observability.