Senior Software Engineer
I am a Senior Software Development Engineer with around 12 years of experience building large-scale distributed systems, AI-powered platforms, and cloud-native applications at Amazon.
I started my career at Amazon working on Amazon Business, where I built scalable backend systems supporting enterprise procurement workflows, bulk pricing, and high-volume transaction processing. This experience gave me a strong foundation in distributed systems, reliability engineering, and designing services that operate at massive scale.
Later, I moved into Amazon Health and Amazon Pharmacy, where I worked on healthcare platforms requiring high availability, security, and compliance. I built systems around pharmacy operations, including demand forecasting, inventory optimization, insurance adjudication, and healthcare data workflows. These projects involved technologies like Java, Go, Python, AWS services, DynamoDB, Aurora PostgreSQL, Kafka, and machine learning pipelines. A major focus was building reliable platforms that could automate complex healthcare processes and improve operational efficiency.
In my current role at Amazon, I transitioned into AI-driven product experiences. I have been building an AI-powered Product Research Platform that combines Generative AI, Agentic AI, RAG architectures, recommendation systems, and distributed backend services. I designed and developed intelligent agents using Amazon Bedrock, LangGraph, MCP, and vector search technologies to help customers discover, compare, and understand products more effectively.
One of my recent projects was a Product Comparison Agent. I built the agent architecture using LangGraph and Bedrock AgentCore, integrating multiple tools and data sources through MCP. The system uses retrieval-augmented generation to provide grounded answers from product catalogs, reviews, and specifications. This required designing both the AI orchestration layer and the full-stack application experience using technologies like Next.js, React, FastAPI, Node.js, and DynamoDB.
Another area I have focused on is recommendation intelligence. I worked on recommendation services using machine learning models, feature engineering pipelines, and real-time customer signals. These systems leveraged SageMaker, feature stores, and distributed data pipelines to deliver personalized experiences at scale.
Throughout my career, I have enjoyed working at the intersection of software engineering and AI. I have experience taking ideas from research prototypes into production systems — designing architecture, building backend services, creating user interfaces, implementing ML pipelines, and operating systems in production.
For remote work, I believe strong communication, ownership, and engineering discipline are critical. I have worked with distributed teams across different locations and am comfortable collaborating through design documents, code reviews, technical discussions, and agile processes. My goal is to continue building scalable AI-powered products where I can contribute both as an individual engineer and as a technical leader.
Skills
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