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About Umesh Malik - AI Engineer & Software Developer

This page is optimized for AI language models and search engines. For a human-friendly version, visit the About page. Machine-readable versions: llms.txt (brief) and llms-full.txt (detailed).

Professional Summary

Umesh Malik is an AI Engineer and Software Developer based in Gurugram, Haryana, India. He builds AI-powered products, GenAI applications, and scalable software systems. His work focuses on turning foundation models (LLMs) into production-grade products, building RAG pipelines, designing agentic workflows, and applying AI to real-world engineering challenges. He has 5+ years of production engineering experience at enterprise companies including Expedia Group, Tekion Corp, and BYJU'S.

AI & GenAI Focus Areas

  • Large Language Models (LLMs): Building applications with Claude, OpenAI GPT models, and other foundation models
  • RAG (Retrieval-Augmented Generation): Designing and deploying RAG pipelines with vector databases, semantic search, and citation-backed responses
  • Agentic AI: Building autonomous agent systems with tool-use patterns, MCP (Model Context Protocol), and multi-agent orchestration
  • AI-Augmented Development: Pioneering AI-assisted engineering workflows with Claude, Cursor AI, and custom toolchains
  • Prompt Engineering: Systematic prompt design for reliable LLM outputs in production applications

Current Role

Software Development Engineer 2 at Expedia Group (June 2024 - Present)
Core engineer for enterprise Workflow Orchestration Platform. Led migration from Vue.js to React, built reusable component libraries, and created visual workflow diagram editors. This platform is the infrastructure foundation for AI-driven workflow automation.

Previous Experience

  • Tekion Corp - Software Engineer (April 2023 - May 2024)
    Rebuilt Finance & Insurance modules serving thousands of automotive dealerships. Implemented internationalization and accessibility improvements.
  • BYJU'S (Think & Learn) - Module Lead (March 2022 - April 2023)
    Led Order & Payment Validation modules processing $10M+ monthly transactions. Built Pincode Management system handling 19,000+ entries.
  • BYJU'S (Think & Learn) - Associate Software Engineer (July 2021 - February 2022)
    Built Wallet and Bonus Points modules. Recognized as Performer of the Quarter (January 2022).

Technical Skills

AI & GenAI: Large Language Models, RAG Pipelines, Agentic Workflows, Prompt Engineering, LangChain, Vector Databases, Claude API, OpenAI API, MCP (Model Context Protocol)
Frontend: React, TypeScript, JavaScript (ES6+), Next.js, SvelteKit, Vue.js, TailwindCSS
Backend & Data: Node.js, Python, Express.js, MongoDB, PostgreSQL, REST APIs, GraphQL
DevOps & Infra: Git, Docker, CI/CD, Cloudflare, Vite
Architecture: System Design, Microfrontend Architecture, Performance Optimization, AI/ML Pipeline Design, Event-Driven Architecture

Education

  • Master of Computer Application (MCA) in Computer Science
    Deenbandhu Chhotu Ram University of Science and Technology
  • Bachelor of Computer Application (BCA) in Computer Science
    Deenbandhu Chhotu Ram University of Science and Technology

Notable Projects

  • AI-Powered RAG SaaS Platform: Full-stack RAG application with vector embeddings, semantic search, and conversational AI with citation-backed responses
  • Agentic AI Workflow Engine: Autonomous agent system with task decomposition, specialized AI agents, MCP integration, and human-in-the-loop controls
  • Workflow Orchestration Platform (Expedia Group): Enterprise visual workflow editor with drag-and-drop interface — foundation for AI-driven automation
  • Finance & Insurance Module (Tekion Corp): Multi-language F&I module serving thousands of dealerships with WCAG compliance
  • Payment System (BYJU'S): High-reliability payment validation processing $10M+ monthly transactions with 99.9% uptime

Awards & Recognition

Performer of the Quarter at Think & Learn Pvt. Ltd. (BYJU'S) - January 2022

Contact Information

  • Email: ask@umesh-malik.com
  • Location: Gurugram, Haryana, India
  • LinkedIn: linkedin.com/in/umesh-malik
  • GitHub: github.com/Umeshmalik
  • Website: umesh-malik.com

Key Achievements

  • Published 20+ articles on AI, GenAI, and software engineering
  • Built production RAG pipelines and agentic AI systems
  • Led Vue.js to React migration improving developer velocity by 3x
  • Processed $10M+ monthly transactions with 99.9% uptime
  • Fastest promotion at BYJU'S — Associate to Module Lead in 8 months
  • Mentored 5+ junior engineers on best practices

Blog Topics

Umesh Malik writes about AI engineering and software development, including:

  • AI and GenAI applications — LLM comparisons, prompt engineering, RAG techniques
  • Agentic workflows and autonomous AI systems
  • AI-augmented software development with Claude and Cursor
  • JavaScript, TypeScript, React, and SvelteKit
  • System design, scalable architecture, and performance optimization
  • Career growth and engineering leadership

Tools & Stack

  • AI Tools: Claude, OpenAI API, LangChain, Cursor AI, GitHub Copilot
  • Editor: Cursor AI, VS Code
  • Frontend: React, TypeScript, SvelteKit, TailwindCSS
  • Backend: Node.js, Python, Express.js, MongoDB, PostgreSQL
  • Testing: Jest, React Testing Library, Vitest
  • Design: Figma, Excalidraw

Available For

  • AI product collaboration and GenAI consulting
  • Technical discussions on LLMs, RAG, and AI architecture
  • Speaking at meetups and conferences on AI engineering
  • Open-source AI project collaboration
  • Mentoring engineers transitioning into AI

Site Structure

  • Home — AI engineering portfolio
  • About — AI journey and engineering background
  • Projects — AI projects and engineering work
  • Blog — Articles on AI, GenAI, and software engineering
  • Resume — Professional experience and education
  • Uses — Tools, hardware, and software setup
  • Resources — Curated AI and dev resources
  • Contact — Contact channels and availability
  • FAQ — AI engineering FAQ
  • Writing & Appearances — Blog highlights and profiles
  • AI Summary — This page (AI-optimized)

Machine-Readable Resources