Hi, I’m Tejas Shetty, a Fresh Master of Computing graduate from ANU (Artificial Intelligence) who enjoys building and shipping reliable software end-to-end. I’ve worked across fullstack and backend systems, integrating external APIs, designing core services, and improving performance with practical engineering choices—whether it’s scaling concurrent workloads or debugging production issues quickly. I also have strong applied AI experience, including LLM-based agentic chatbot integration, RAG-style workflows, and computer vision models like YOLO for defect detection. I love taking ownership of what I build, learning new tools fast, and turning messy real-world constraints into clean, measurable outcomes—ideally in a team where I can contribute from day one and keep leveling up.

Tejas Shetty

Hi, I’m Tejas Shetty, a Fresh Master of Computing graduate from ANU (Artificial Intelligence) who enjoys building and shipping reliable software end-to-end. I’ve worked across fullstack and backend systems, integrating external APIs, designing core services, and improving performance with practical engineering choices—whether it’s scaling concurrent workloads or debugging production issues quickly. I also have strong applied AI experience, including LLM-based agentic chatbot integration, RAG-style workflows, and computer vision models like YOLO for defect detection. I love taking ownership of what I build, learning new tools fast, and turning messy real-world constraints into clean, measurable outcomes—ideally in a team where I can contribute from day one and keep leveling up.

Available to hire

Hi, I’m Tejas Shetty, a Fresh Master of Computing graduate from ANU (Artificial Intelligence) who enjoys building and shipping reliable software end-to-end. I’ve worked across fullstack and backend systems, integrating external APIs, designing core services, and improving performance with practical engineering choices—whether it’s scaling concurrent workloads or debugging production issues quickly.

I also have strong applied AI experience, including LLM-based agentic chatbot integration, RAG-style workflows, and computer vision models like YOLO for defect detection. I love taking ownership of what I build, learning new tools fast, and turning messy real-world constraints into clean, measurable outcomes—ideally in a team where I can contribute from day one and keep leveling up.

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Experience Level

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Work Experience

Software Developer – ANU TechLauncher Industry Capstone at Bardar (bardar.online)
July 1, 2025 - June 30, 2026
Built a NestJS backend from scratch, owning 10+ REST APIs for artist discovery, geo-sync, genre filtering, and head-to-head comparisons. Integrated with source APIs and deployed the system on Heroku using CI/CD pipelines. Designed a log-scaled artist scoring algorithm to rank thousands of artists across any city globally. Architected a priority task queue and per-API rate limiter to coordinate concurrent external API calls, reducing search latency by 20–30% and preventing pipeline breakages under concurrent load. Led end-to-end integration of an agentic AI chatbot (Gemini 2.5 Flash) with access to backend tool calls, enabling natural language artist discovery and dynamic rendering of rich UI cards from API responses.
Data Science and Backend Intern at Axiscades Technologies Ltd
February 1, 2024 - July 31, 2024
Delivered Python/Flask backend APIs and built a QR-based inventory system to automate industry inventory workflows, reducing processing time by 25%. Implemented YOLO-based defect detection pipelines for production line quality control, identifying assembly errors and container defects, reducing error rates by 60%.
Undergraduate Research Intern (Data Science) at Indian Space Research Organisation (ISRO)
February 1, 2023 - February 29, 2024
Designed and deployed ML models (CNNs, Autoencoders, Random Forest) across 50+ configurations to optimize satellite mission operations, improving operational efficiency by 30%. Developed predictive maintenance workflows using expert systems and machine learning to detect satellite part failures with 85% accuracy, reducing maintenance downtime by 25%.

Education

Master of Computing (Specialization: Artificial Intelligence) at Australian National University
July 1, 2024 - June 30, 2026
Bachelor of Engineering in Computer Science at M.S. Ramaiah Institute of Technology
November 1, 2020 - May 31, 2024

Qualifications

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Industry Experience

Software & Internet, Education, Government, Computers & Electronics, Media & Entertainment