Anirudh Agarwal

About Anirudh Agarwal

I\'m a backend engineer who genuinely enjoys building things that scale — not just writing code that works, but designing systems that hold up when traffic spikes, data grows, and edge cases you didn\'t anticipate start showing up in production.Currently SDE-2 at Gartner, where I\'ve spent the last couple of years working on distributed systems, ETL pipelines, and CI/CD infrastructure. One of the things I\'m most proud of — led a Jenkins to CloudBees migration that cut deployment times by 73% and artifact storage by 67%. Not glamorous on paper, but it meaningfully changed how fast the team could ship. Also built real-time event-driven data pipelines on AWS (SQS + EventBridge) and Spring Batch ETL systems processing millions of records for BI and sales reporting.My core stack is Java, Spring Boot, and AWS — but I care more about the problem than the language.Outside of work I take DSA seriously. Codeforces Expert, max rating 1714, ranked 667 out of in a rated contest. It\'s kept my problem-solving sharp in a way that directly shows up in how I approach system bottlenecks and optimization challenges at work.Lately I\'ve been going deep on the AI tooling side — not just using ChatGPT for quick answers, but actually setting up and running local LLM environments, working with RAG pipelines, and using agentic dev tools like OpenClaw daily to automate workflows that used to eat up hours. I think the engineers who figure out how to multiply their output with AI right now are going to have a serious edge in the next few years — and I want to be one of them.

Experience

1. Software Engineer

   Gartner

   Apr 2023 — Present · Gurugram, IN

   Spearheaded Jenkins-to-CloudBees CI/CD migration across microservices, reducing deployment time by 73% and artifact storage by 67% by replacing environment-specific Docker builds with single universal image using runtime Kubernetes env injection∙ Debugged and resolved critical production configuration issue where environment variables weren’t resolved at runtime, implementing JVM property injection via Tomcat’s setenv.sh to bridge Kubernetes environment variables to Spring Boot property resolution∙ Built real-time data ingestion pipeline on AWS using SQS and EventBridge with Long Polling, reducing redundant API calls and costs while maintaining low-latency transfer from Athena to downstream analytics.∙ Designed and delivered end-to-end ETL pipelines using Spring Batch and PL/SQL syncing Eloqua data to BI systems, enabling automated reporting that directly supported sales operations.

Education

• Institute of Engineering and Technology

  Bachelor of Technology - BTech, Computer Science

  2017 — 2021