Harsh Artwani

About Harsh Artwani

I build systems that bridge the gap between human intent and machine execution. In my 2.5+ years at Paycom, I have evolved from developing core HR features to architecting AI-powered services that redefine how millions of users interact with enterprise data. My focus is on creating high-throughput, low-latency systems that are as reliable as they are innovative.What drives my work:Intelligent Automation: I specialize in translating complex AI commands into deterministic workflows. My recent work on the iWant AI assistant focused on intent validation and secure data retrieval, significantly streamlining how users access critical information.Architectural Scalability: I am passionate about the \"behind-the-scenes\" infrastructure that keeps platforms stable. This includes leading NoSQL (Couchbase) integrations and managing distributed microservices on Kubernetes to ensure fault tolerance and high performance.Efficiency at Scale: Whether it’s reducing system downtime through deep log analysis or optimizing React frontends for responsiveness, I look for bottlenecks and eliminate them.I am a lifelong learner who thrives in Agile environments, moving fluidly between C#, PHP, Java, and Python to solve whatever problem is at handBeyond the Code: I’m a Chess player, Calisthenics enthusiast, and Soccer fan. Whether it\'s the strategy of a gambit, the discipline of a workout, or the teamwork on the pitch, I bring that same focused energy to my agile development teams.Let’s connect to talk about scalable architecture, distributed systems, or your favorite soccer club!

Experience

1. Software Developer Iv

   Paycom

   Jan 2025 — Present · Dallas-Fort Worth, TX, US

   Built and tested backend services for Paycom’s AI assistant (iWant), including intent validation, permission checks, and GraphQL resolvers, translating AI commands into deterministic workflows, enabling users to access critical information instantly and reducing manual search time by 70%, delivering secure, reliable Copilot-style decision supportDesigned and led a modular Couchbase (NoSQL) integration enabling low-latency, high-throughput data access, caching, and distributed locking across services, improving scalability, maintainability, and cross-module reuse by 40%, while enabling faster adoption through clear documentation and usage patternsEnhanced platform reliability by proactively resolving critical production issues through deep analysis of Kubernetes and Splunk logs, reducing system downtime, improving stability, and increasing user satisfaction by 25%Optimized frontend performance using lazy loading, code splitting, and React component improvements, significantly enhancing UI responsiveness and user experience for millions of users while collaborating with a 6-member cross-functional teamBuilt an admin-level, cross-module process and step tracker using Couchbase to monitor long-running workflows, capture failures, and enable safe retries, improving system reliability and operational visibility for cross-team debuggingImproved release quality by designing and executing Artemis automated tests and regression suites, ensuring thorough coverage of critical workflows and reducing post-release defects by 35%

Education

• Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore

  Bachelor of Technology - BTech, Information Technology

• The University of Texas at Arlington

  Master of Science - MS, Computer Science