San Francisco Bay Area
Software Engineer at Amazon Web Services (AWS) focused on designing and operating large-scale distributed systems, cloud platforms, and AI-driven developer infrastructure. I work on Tier-1 systems requiring high availability, scalability, consistency, and operational excellence, where I regularly solve ambiguous engineering problems and drive solutions from architecture to production deployment. My work spans backend platforms, distributed microservices, infrastructure automation, AI systems, and intelligent workflow orchestration. In addition to building reliable cloud-native systems, I actively design and develop multi-agent AI architectures, autonomous workflows, retrieval-augmented systems, and developer productivity solutions powered by modern LLM ecosystems. I have strong experience building agentic AI systems capable of code understanding, repository navigation, reasoning across large codebases, tool execution, memory management, and long-running orchestration workflows. I work extensively with AI infrastructure patterns including LangGraph, agent orchestration frameworks, retrieval pipelines, vector search systems, context engineering, inference workflows, and scalable data processing architectures. I enjoy operating in high-ownership environments where problems are loosely defined but technically challenging. My strengths include system design, production-scale engineering, debugging complex distributed systems, driving architectural improvements, and rapidly turning ideas into production-ready platforms. Technical areas of interest: • Distributed Systems & Cloud Infrastructure • Multi-Agent AI Systems & Autonomous Workflows • LLM Applications & Agent Orchestration • AI Infrastructure & Retrieval Architectures • Backend Platforms & Scalable APIs • Data Pipelines & Workflow Automation • Kubernetes, CI/CD & Infrastructure Reliability • Production Observability & Operational Excellence Technologies & frameworks: Java, Golang, Python, C++, JavaScript/TypeScript, Node.js, React, Angular, Kubernetes, Docker, AWS, LangGraph, AI agent frameworks, vector databases, distributed workflows, microservices, REST/gRPC APIs, CI/CD systems, and modern cloud-native architectures.
- Developed a multi-agent AI system that simulates key phases of the software development lifecycle through specialized collaborating agents, exploring the application of agentic AI techniques to software engineering workflows and developer productivity. - Spearheaded organization-wide initiatives to achieve near-complete automation of Amazon Redshift region builds, driving the development of hundreds of automation tools, delivery pipelines, testing frameworks, and operational workflows across multiple infrastructure domains. - Partnered with 10+ engineering teams to standardize automation strategies, eliminate manual operational processes, and accelerate infrastructure deployments. Led technical discussions, coaching sessions, architecture reviews, demos, and knowledge-sharing programs to drive adoption at scale. - Contributed to the development and launch of Redshift's cross-cluster data sharing capabilities, enabling seamless data sharing across both provisioned and serverless Redshift environments as part of major customer-facing platform enhancements. - Led the re-architecture of a large-scale script execution platform from the ground up, managing a team of four engineers to build a distributed execution engine capable of operating across more than 500,000 Redshift instances. - Designed and delivered highly scalable distributed systems, orchestration services, and infrastructure automation platforms that improved reliability, operational efficiency, and deployment safety for mission-critical cloud infrastructure. - Mentored engineers and interns while influencing technical direction through architecture reviews, cross-team collaboration, operational excellence initiatives, and long-term platform strategy.
- Led the development of a Tier-1 orchestration platform that powers the provisioning and lifecycle management of millions of Amazon Redshift customer instances each year. - Owned the design and implementation of distributed services and workflow orchestration systems, driving improvements in scalability, reliability, deployment safety, and operational excellence across critical infrastructure. - Delivered strategic platform initiatives including release automation, resource lifecycle management, operational tooling, and centralized configuration/orchestration systems used by multiple Redshift services and engineering teams. - Influenced technical direction through architecture reviews, cross-team collaboration, operational excellence initiatives, and mentorship of engineers and interns.
- Designed and developed mega-scale distributed scripts execution engine and backend services for Amazon Redshift, improving service reliability, operational efficiency, and customer experience across distributed cloud infrastructure. - Built hundreds of automation frameworks that improved compliance with operational standards while minimizing manual intervention for engineering and operations teams. - Developed an internal platform used by engineers, managers and oncalls to monitor, diagnose, and manage Redshift infrastructure and service workflows, helping reduce operational friction and improve incident response efficiency. - Collaborated closely with software engineers, service owners, and operations teams to design scalable solutions for infrastructure management, system observability, and operational workflows. - Implemented backend services, APIs, and workflow orchestration components supporting high-availability distributed systems running at AWS scale. - Participated in end-to-end software development lifecycle activities including architecture discussions, design reviews, implementation, testing, production deployments, and operational support.
A) Core Banking Team - Worked on the backend system of core banking functionality that provides an available and consistent solution to our clients. - Developed various backend APIs, enhanced existing functionality, debugged loopholes, monitored the system's state at the infra level, and participated in numerous production deployments. (B) OpsInfra Team - Worked on the backend system of a custom deployment product used in-house to deploy a dynamic set of services in one click on any cloud infrastructure. - This automatic deployment system reduces issues like inter team dependency, incidents, issue tracking, status management, etc. and completes a manual task of 1-1.5 months automatically in hours.
- Developed a responsive Mean stack application with admin panel - Using admin panel, website content, images, SEO tags, links, etc. can be altered. - MongoDB Database was used to serve the purpose. - NodeJs server was used for website in AWS EC2.