AI Backend &
Systems Engineer
Building scalable GenAI infrastructure, LLM workflows, agents, and distributed backend systems using NestJS, LangGraph, Rust, and vector search.
About Me
Get to know more about me, my background, and what drives me.
AI Backend & Systems Engineer
I design and build high-performance backend systems and scalable AI infrastructure. My expertise lies in architecting distributed systems, optimizing low-latency workflows, and productionizing Large Language Models (LLMs) for real-world applications.
I specialize in the intersection of Backend Engineering and Generative AI. I have built agentic workflows using LangGraph, scalable microservices with NestJS and Rust, and retrieval systems using vector databases. My focus is on reliability, concurrency, and system design patterns that stand up to production traffic.
Currently, I am deepening my work in multi-agent systems and event-driven architectures. I am actively building tools that bridge the gap between experimental AI scripts and robust, enterprise-grade platforms.
I am open to roles in AI Infrastructure, Backend Engineering, and Distributed Systems, where I can solve complex architectural challenges.
Education
Bachelor's of Technology in Computer Science
Year of Graduation: 2027
Location
Based in Odisha, India
Open to Hybrid/Remote Opportunities
Interests
Blockchain • Low Latency Programming • Open Source Contributor • System Design • Cloud Architecture • AI/ML Integration
Philosophy
I believe in continuous learning and building solutions that make a real difference. My approach combines technical excellence with user-centered design to create meaningful experiences.
Technical Arsenal
A comprehensive overview of my technical skills and competencies, focused on high-performance and scalable systems.
AI & LLM Systems
- LangChain
- LangGraph
- Agents
- RAG
- Vector Databases
- Memory Systems
Backend & Systems
- NestJS
- Node.js
- Rust
- System Design
- REST APIs
- Async Systems
Distributed Systems
- Microservices
- Caching Strategies
- Event-Driven Architecture
- Concurrency
- Message Queues
Infrastructure
- AWS
- Docker
- Kubernetes
- CI/CD
- Terraform
- Linux
My Projects
A curated selection of my technical projects showcasing my skills and expertise.
The Problem
Developers struggle to manually migrate legacy codebases between languages while preserving logic.
Challenge
Parsing ASTs accurately and maintaining context across large files was computationally expensive and error-prone.
Solution
Built a VS Code extension using Gemini 2.0 Flash API for context-aware translation. Implemented optimized caching for repetitive code blocks and streaming responses for lower latency.
The Problem
Monitoring microservices across fragmented cloud environments is complex and lacks unified visibility.
Challenge
Aggregating metrics, logs, and traces from distributed clusters in real-time without adding latency.
Solution
Architected a full-stack observability suite integrating Prometheus & Grafana. Automated deployment pipelines using ArgoCD and Helm charts on Kubernetes.
The Problem
Standard shells can be slow and lack modern, improved developer experience features.
Challenge
Managing low-level process control and memory safety while ensuring high throughput.
Solution
Engineered a custom shell in Rust with a custom-built parser and job control system. Achieved 20% faster startup time compared to Zsh by optimizing resource allocation.
The Problem
Handling concurrent audio streams and metadata synchronization at scale is resource-intensive.
Challenge
Ensuring consistent state across distributed content delivery nodes and managing container orchestration.
Solution
Deployed a containerized microservices architecture on AWS EKS. Utilized S3 for object storage and implemented a custom load balancing strategy for media streaming.
The Problem
Centralized password managers are vulnerable to single points of failure and data breaches.
Challenge
Securely storing credentials without the server ever having access to the encryption keys.
Solution
Implemented a zero-knowledge architecture using client-side AES-256 encryption. Backend (Node.js) only stores encrypted blobs, ensuring complete data privacy.
Experience & Education
My professional journey, academic background, and continuous learning path.
Work Experience
SDE Intern (Backend Systems)
Architected the core video streaming pipeline for a decentralized media platform. Designed a microservices-based backend using NestJS to handle high-concurrency video encoding and delivery. Implemented Redis caching layers to reduce database load by 40% during peak traffic.
Backend & Infrastructure Engineer
Designing and deploying scalable backend solutions for diverse clients. Migrating legacy monolithic applications to containerized microservices on Kubernetes. Implementing CI/CD pipelines using GitHub Actions and conducting load testing to ensure 99.9% uptime availability.
Backend Engineer Intern
Engineered secure payment processing services integrating multiple gateways (Razorpay, PhonePe) with transactional integrity. Optimized database queries in MongoDB, reducing validation latency by 30%. Developed standard REST APIs for merchant dashboard analytics.
Technical Educator (Systems & Algo)
Creating advanced technical content on Distributed Systems, Rust, and Data Structures. Mentoring students on low-level programming concepts, memory management, and concurrent algorithm design.
Education
BTech in Computer Science and Engineering
NIST University
Focusing on computer science fundamentals, data structures, algorithms, computer architecture and software engineering principles.
Certifications
Data Structures and Algorithms
IT World Education • 2023
Full Stack Web Development
100xDevs • 2022
Cloud Computing and DevOps
IT World Education • 2022