Backend & AI
Systems Engineer
I build scalable backend systems, AI-powered applications, and cross-platform mobile experiences. Specializing in Python APIs, LLM-driven multi-agent systems, and cloud-native architectures with Azure and AWS. Currently pursuing a Master's in Applied Computing, researching NLP and sentiment analysis for STEM education.
Projects
Cross-platform mobile application that allows users to privately share and store photos with a partner or friend. Built with Expo and Firebase for secure authentication, cloud storage, and real-time sync.
- Private shared gallery between two users
- Photo uploads with Firebase Storage
- Secure auth with Firebase Auth and real-time Firestore
- Push notifications via Firebase Functions
- Automated CI/CD with GitHub Actions and Expo EAS
AI-powered application that generates personalized Spotify playlists from natural language prompts using multi-agent orchestration to collaboratively select and verify songs.
- Multi-agent orchestration with Agno and OpenAI
- Playlist generation from natural language prompts
- Spotify API integration for song verification
- Direct export to user Spotify accounts
- Automated deployments via Railway and Vercel
Master's thesis research developing an NLP system that applies sentiment analysis and machine learning to detect academic stagnation in STEM students — enabling early educational intervention before students disengage.
- Sentiment analysis pipeline for educational text data
- ML classification models to identify stagnation patterns
- Feature engineering from student activity and feedback
- End-to-end Python pipeline for data processing and model evaluation
Containerized finance application with a Streamlit interface and Flask API, cleanly separating business logic from presentation while staying lightweight and reproducible.
- Dashboard with metrics and interactive charts
- Transaction, category, and account tracking
- Credit card purchases and installment handling
- Monthly progress summaries and balance reporting
- Portable local setup with Docker Compose
Education
Core Skills
Experience
- Developed a robust Python API using AIOHTTP to access Azure services — CosmosDB, Blob Storage, and Key Vault.
- Integrated Microsoft Authentication and JWT for secure access and role-based authorization.
- Implemented JSON schema-based configuration versioning in a multi-agent AI environment.
- Built APIs to dynamically create, update, delete, and manage AI agents.
- Engineered context versioning and templating mechanisms for rollback and template-based agent creation.
- Implemented a context recovery system for AI agents to maintain conversation continuity and context persistence across sessions.
- Built Python utilities to add temporal awareness to agent data retrieval and interpretation.
- Integrated secure Azure Key Vault secret management for agent configuration workflows.
- Implemented access-control measures to define which users can interact with specific agents.
- Developed backend features using Python, Flask, and REST APIs to support engineering workflows.
- Built APIs to support LLMs deployed with Hugging Face TGI and vLLM in Docker containers on AWS EC2.
- Created React UI components for improved data input and result visualization.
- Implemented backend logic to store structured AI outputs in SQL databases.
- Integrated EMON for system performance analytics and profiling workflows.
- Built AI agents using orchestration across multiple LLM providers to improve automation capabilities.
- Wrote optimized SQL queries for large Azure datasets to improve query performance.
- Created automated ETL pipelines for streamlined data ingestion and processing.
- Improved data quality through validation checks and transformation workflows.
- Managed Azure SQL environments to support reliability and scalability.
Contact
Open to backend, AI systems, and full-stack software engineering opportunities. Let's build something great together.