Basavraj Chinagundi

MS Computer Science student at Arizona State University with two years of industry experience building AI-powered tooling and data pipelines at Deloitte. I gravitate toward backend problems: wiring up LLM workflows, writing ETL that doesn't silently break, and making internal tools that people actually use. I also like building things fast at hackathons and have two first-place finishes to show for it.

I'm actively seeking Summer 2026 internships in SWE/ML/Backend roles.

Education

M.S. Computer Science - Arizona State University

Aug 2025 – May 2027 • GPA: 4.0 / 4.0

Coursework: Natural Language Processing, Data Processing at Scale, Data Mining, Semantic Web Mining, Knowledge Representation.

B.E. Electronics & Communication - Thapar Institute of Engineering and Technology

Aug 2019 – July 2023 • GPA: 8.62 / 10.0

Technical Skills

Languages

PythonSQLJavaScriptTypeScriptJavaC++Bash

AI / ML

PyTorchLangChainLangGraphHugging FaceOpenAIGemini

Frameworks

FastAPIFlaskStreamlitReactSpring Boot

Data & Cloud

AWSSnowflakeDatabricksPostgreSQLMySQLGoogle CloudAzure

Tools

GitDockerPostman

Experience

Deloitte - Analyst, AI & Data

Oct 2023 – July 2025

Worked on AI tooling and data engineering for internal teams. Most of my work involved using LLMs to automate repetitive processes and writing pipelines that moved data across cloud platforms.

• RAG Chatbot: Built a chatbot using Python, Streamlit, and GPT-4 over consolidated banking documents with token-aware chunking and async API calls to handle large document collections.
• Code Generation Pipeline: Developed an XML-to-SQL pipeline using GPT-4.1 to parse Informatica ETL mappings and generate executable SQL scripts for legacy system migration.
• Data Quality Automation: Automated rule generation using Great Expectations and Gemini 2.0, producing validation rules from schema metadata for data engineering pipelines.
• ETL Pipelines: Wrote Python ETL pipelines for multi-cloud data extraction from GCP and Azure, loading processed data into Snowflake and Databricks.
• Agentic Workflow: Integrated four generative AI tools into a unified workflow using LangGraph, routing tasks across services based on input type and context.

Samsung SDS - Software Development Engineer Intern

Mar 2023 – Jun 2023

• Inventory Tracking Tool: Programmed a full-stack CRUD app using Java, Spring Boot, and React with RESTful APIs, replacing manual SKU data entry for the operations team.
• Demand Forecasting: Prototyped a forecasting model using ARIMA and Prophet in Python, analyzing seasonal trends in inventory data to support replenishment planning.

Projects

Connect

Email: bchinagu@asu.edu
LinkedIn: linkedin.com/in/basavrajchinagundi
GitHub: github.com/raj-chinagundi