Professional Summary
Pre-final year B.Tech CSE student specializing in AI Product Engineering and Application Design. Experienced in building end-to-end AI applications, integrating API models, managing prompt pipelines, and structuring failover execution schemas. Proficient in Python, FastAPI, and Streamlit, with a focus on developer efficiency and rapid system prototyping. Demonstrated ability to translate raw algorithmic models into highly available, user-centric AI solutions.
Education
B.Tech in Computer Science & Engineering (Specialization: Cloud Computing & Machine Learning)
- Academic Standings: CGPA: 8.0+ / 10. Relevant Coursework: AI Systems Design, Cloud Services, Data Structures & Algorithms, Database Management, Python.
Technical Skills
AI & System Design:
LLM Application flows, API Integrations, Prompt Engineering, Fallback Systems, Error Boundary Controls
Libraries & Modeling:
Python, FastAPI, Streamlit, Pandas, NumPy, Scikit-learn (ML Inferencing Pipelines)
DevOps & Deploy:
Git, GitHub Actions (CI/CD Automations), Docker Containerization, Vercel, Render Cloud Platforms
Languages & Core:
Python, SQL, C, API Request Parsing
Projects
System Design, Prompt Pipelines, Failover Logic, Python, REST API
- Designed the end-to-end system architecture of an AI-powered legal consultation app, establishing validation logic gates.
- Created a custom failover logic loop ("Raksha Mode") to catch API interruptions and route request tokens to backup handlers.
- Presented the MVP deployment scaling layout at the ENTREPRENIA 2025 startup showcase, achieving competition finalist status.
Python, Streamlit, Vercel, GitHub Actions, CI/CD Pipeline
- Developed and launched a real-time predictive dashboard with Streamlit, serving inference calculations immediately.
- Constructed backend model pipelines with Scikit-learn, configuring data validation checks on runtime queries.
- Automated version check updates and static testing routines by writing custom GitHub Action deployment pipelines.
Experience & Open Source Contributions
- Leveraged AI assistance (GitHub Copilot) to accelerate coding speed, reducing time-to-MVP for small projects by 3x.
- Maintained 10+ public GitHub repositories showcasing structured API schemas, reproducible setups, and automated testing logs.
- Participated in competitive programming in Coderush 2.0 (2025), optimizing performance constraints under pressure.