About Shreya
Hi! I'm Shreya — a backend-focused full stack developer and AI engineer who loves problems that don't have neat answers.
My work spans trimodal UAV detection (~97.6% accuracy on Jetson edge devices) and building payment/CRM microservices that handle 100+ daily transactions and cut manual effort by ~40%.
I'm currently open to SDE / Backend Engineer roles for the 2026 batch. I build Spring Boot microservices, secure REST APIs, and AI features using LLM tool-calling, prompt engineering, and LLMOps.
Education
Bachelor of Technology in Computer Science and Engineering
Birla Institute of Technology, Mesra
Nov 2022 – June 2026
CGPA: 8.27/10.0 | Software Engineering, DSA, DBMS, OOP, Computer Networks, Operating Systems, and Machine Learning.
Higher Secondary Education (ISC)
Motilal Nehru Public School, Jamshedpur
2019 – 2021
Completed with focus on English, Mathematics, Computer Science and Pure Science.
Skills & Interests
Backend & Microservices
• Java, Spring Boot, REST APIs, and microservices
• API Gateway + service discovery patterns
• JWT authentication + RBAC and secure-by-design APIs
AI / GenAI Engineering
• LLM tool-calling, prompt engineering, and LLMOps
• LLM BI agent patterns (GraphQL + tool orchestration)
• Edge AI deployment + inference optimization (Jetson)
Databases, Cloud & DevOps
• MySQL, PostgreSQL, and MongoDB (modeling + optimization)
• Docker / Docker Compose and production deployment workflows
• AWS fundamentals (EC2, S3, RDS) + Postman + Linux
Projects
CareerHub
10+ Spring Boot microservices with API Gateway + service discovery, plus LLM resume analysis and a 400+ DSA module—built to help users learn and ace interviews.
Synapse-IQ
An LLM BI agent using tool-calling + GraphQL for real-time insights across datasets, with multi-provider fallback and ~60% token reduction.
AstraStay
Hotel booking backend: complete booking lifecycle APIs with JWT + RBAC, concurrency-safe reservation logic, and secure REST endpoints.
What I'm Learning
Technical Skills
- • System design for scalable microservices
- • LLM tool-calling, RAG patterns, and LLMOps
- • Edge AI deployment + inference optimization
- • AWS fundamentals and production deployment workflows
- • Data modeling, indexing, and query optimization
Personal Development
- • Shipping production-ready features
- • Debugging under pressure and reliability mindset
- • Clean architecture and testable code
- • DSA practice (550+ problems)
- • Continuous learning through real projects