Mohit Avadhanula

AI Engineer @ Incrivelsoft LLC.

About

👋 About Me: Hi there! My name is Mohit Avadhanula, and I'm a software engineer passionate about building systems that solve real problems using ML and AI Agents. 📚 Education: I'm a Computer Science M.S. student at Georgia Tech. I recently completed my B.S. in Computer Science & IT Management at UC Santa Cruz. 💻 Skills: Through internships, research, and personal projects, I've developed proficiency in Python, Java, C, C++, and SQL. I have experience building backend systems with Flask and Django, working with cloud platforms like AWS and GCP, and developing ML models using scikit-learn, HuggingFace, and FinBERT. I've also worked extensively with REST APIs, PostgreSQL, and CI/CD pipelines. 💼 Experience: I am current AI Engineer at Incrivelsoft. I've interned at Sidepocket Financial (backend dev, ETL pipelines, financial APIs) and Incrivelsoft (validation engines, NLP integration). I also spent time as a Quantitative ML Researcher at UC Santa Cruz, building trading models and data pipelines. 🎯 Hobbies: I've been dancing Bollywood and hip hop throughout college and still going strong. I'm passionate about bodybuilding and nutrition, and I'm currently getting into making house music with hopes of DJing. I'm also an avid car enthusiast who loves connecting with fellow gearheads online and at local car meets.

Country

United States

City

San Francisco Bay Area

Industry

Computer Software

Skill

Anthropic Claude, MongoDB, FastAPI, REST APIs, Unit Testing, Natural Language Processing (NLP), Agentic AI Development, BERT (Language Model), Hugging Face Products, Sentiment Analysis, Amazon Redshift, PySpark, Amazon S3, Amazon Web Services (AWS), Databricks Products, Least Squares Regression, R (Programming Language), lasso regression, Random Forest, OpenAI API

Experience

AI Engineer

Incrivelsoft LLC.

2025-9 - Present · 1 yr 1 mo

San Francisco Bay Area

• Architected agentic content recommendation system for a maternal healthcare platform using the Anthropic API, aggregating YouTube, news, and social media results to deliver trimester-specific prenatal health content • Reduced recommendation latency by 27% via parallelized content retrieval across 3 API sources, and cut per-request token usage by ~20% through iterative prompt optimization while maintaining relevance • Designed modular tool interfaces with per-source output contracts, enabling teammates to integrate retrieval tools into their own features; persisted user favorites in MongoDB for engagement-driven personalization

Backend Developer

Sidepocket

2024-8 - 2024-11 · 4 mos

San Francisco Bay Area

• Built 3 ETL pipelines using Flask and Django to pull in financial data from Plaid and Apex for real-time Net Asset Value(NAV) calculations across 20+ client portfolios • Automated reporting workflows in Python, cutting manual work by 60% and shrinking delivery time from 2 days to 4 hours • Developed JWT-secured REST APIs with 95% test coverage—zero security issues across 8 production endpoints • Used mocking and factory patterns to make testing cleaner and boosted CI/CD reliability by 25%

Software Developer

Incrivelsoft LLC.

2023-8 - 2023-11 · 4 mos

San Francisco Bay Area

• Built a Python validation engine to verify token legitimacy across multiple games—handled 5,000+ daily transactions with 98% accuracy • Integrated OpenAI's API for NLP-powered rule analysis, which cut down manual review time by 40% on tricky edge cases • Wrote 80+ unit tests using pytest to catch bugs early and keep the codebase reliable • Worked in Agile sprints using Jira, got comfortable with standups, sprint planning, and collaborating across Slack/Outlook