AI Engineering candidate in Chennai, Tamil Nadu, India

Summary

An AI Developer and IIT Madras graduate with a strong foundation in Computer Science and Engineering. He completed his Bachelor of Technology in 2023, securing a top 0.7% rank in JEE Mains and top 0.4% in JEE Advanced among over a million candidates. His academic background includes relevant coursework in Data Structures, Algorithms Analysis, System Design, and Machine Learning.
Professional Experience
AI Developer | Mindgate Solutions (Jul 2024 Present)
He is currently works as an AI Developer, where he was recognized as the 'Best Performer' among 20+ new joiners in the product backend team for the 2024-25 period. His key contributions include:
* RAG System Development: Designed and deployed a production-ready modular RAG system using LangGraph, OpenRouter, and Qdrant, which reduced internal support query resolution time by 60%.
* System Architecture: Engineered a domain-based subagent architecture capable of real-time streaming with 99.9% uptime.
* Optimization: Integrated Qdrant vector store with PostgreSQL to support 10k+ concurrent queries with low latency (<5000ms) and developed Java payment services that optimized cross-currency backends, reducing latency by 35%.
Research Associate | CODIIS (Aug 2023 Apr 2024)
Prior to Mindgate, he focused on system performance and stability.
* Server Optimization: Managed Linux media servers, improving performance by 5% while ensuring 100% server uptime through effective cross-functional collaboration.
* Protocol Evaluation: Evaluated communication protocols to significantly reduce system latency and improved data transfer speeds by 7% using OSI model techniques.
Key Projects
Has demonstrated his technical versatility through several complex projects:
* Real-Time Exchange: Developed a Node.js/TypeScript REST API and a Redis pub/sub matching engine capable of processing 1000+ orders per second with 99% accuracy. This project also included a React interface that boosted user retention by 20%.
* Zapier Clone: Built a scalable webhook service handling 10k+ triggers and engineered a Kafka integration to handle 1M+ events/month. He utilized Zod for validation to reduce errors by 40%.
* Infra Automation: Orchestrated infrastructure using Terraform and GitHub Actions to streamline the creation of VPCs and EC2 instances on AWS, promoting Infrastructure as Code (IaC) best practices.
Technical Skills
* Languages: C++, Java, JavaScript, TypeScript, SQL, HTML/CSS.
* AI & LLM Tools: LangGraph, OpenRouter, Qdrant, RAG, Vector DBs, Prompt Engineering.
* Technologies: Spring Boot, ReactJS, Next.JS, NodeJS, Docker, K8s, AWS, Terraform.

Expectations

1. Advanced AI & RAG Challenges
You should expect a role that moves beyond simple API wrappers to complex, architectural AI problems.
* Target Work: Designing multi-agent systems and modular RAG architectures similar to the "Subagents" system you deployed using LangGraph and OpenRouter.
* Tech Stack: Opportunities to utilize specialized vector databases (like Qdrant) and advanced orchestration tools rather than just standard CRUD applications.
2. High-Scale Engineering & Optimization
Given your history of optimizing latency and handling high throughput, you should look for environments where performance is critical.
* Scale: Systems handling significant load, comparable to the 10k+ concurrent queries or 1M+ monthly events you have previously engineered.
* Impact: Roles that value optimization, where you can apply your skills in reducing query resolution times (as you did by 60%) and cutting latency (as you did by 35% in payment services).
3. End-to-End Ownership (DevOps to Code)
You have demonstrated the ability to manage the entire lifecycle of a feature, and your next job should respect and utilize this versatility.
* Scope: Responsibility that spans from infrastructure automation (Terraform, AWS, GitHub Actions) to backend logic and frontend integration.
* Autonomy: A culture that allows you to own solutions fullydeploying fixes and ensuring stability (99.9% uptime) rather than just handing off code.
4. High-Performance Culture
As a recognized "Best Performer" and top-tier engineering graduate, you should expect a peer group that matches your caliber.
* Environment: A team that values technical excellence and reliability, similar to the environments where you achieved 100% production issue resolution.
* Growth: A clear path to Senior Engineer or System Architect roles, leveraging your background in System Design and Algorithms.