Employment History

Independent software engineer, specialized in AI agentic systems and machine learning

• Implementing agentic systems, including real-time data processing and graph-based models

• Developing integrated data flows and information processing systems, providing real-time feedback and productivity from AI agents

• Industries: SaaS for sales, SaaS for business process management

Cloud platform for AI customer communication. Backed by YCombinator, Google Ventures, Accel, IVP

• Engineering agent AI messaging systems, achieving 2x/second live communication with human customers

• Translated cutting-edge research papers (HumanEval, Tau Bench) into novel custom evaluation tools that benchmarked and guided safe AI Agent development

• Created hallucination detection and mitigation tools, resulting in 98% reduction in error cases (~50 daily errors => 1)

• Architected and lead development of human-in-the-loop AI information system: teaching AI agents to recognize gaps in information, reach out for help, and enabling Podium customers to guide and steer AI behaviors during uncertainty

• Created DevOps infrastructure for event-driven message systems, communicating between local and deployed Kafka and Kubernetes, reducing deployment time by over 90%

• Technologies: LangChain, LangGraph, FastAPI, Kafka, Redis, Kubernetes, Gitlab, Elasticsearch, SQL (Postgres, pgVector), Python

Series C startup from MIT - an IoT and cloud platform for manufacturing data and operations. Backed by E14 Fund, Vertex Ventures, DMG MORI, Insight Partners, TIME Ventures

• Created statistical control toolkit for cloud analytics (fullstack), viewed 600+ times per day in factory operations

• Developed query language tools for manufacturing customers to query and visualize data

• Expanded ETL data pipelines for internal analytics to process 11M+ records daily

• Deployed ML microservice for forecasting and anomaly detection

• Architected and engineered RESTful HTTP microservice for managing NoSQL database

• Technologies: MLFlow, MLServer, Scikit-Learn, Prophet/NeuralProphet, ONNX, Airflow, AWS Redshift, Typescript (Node.js, React), MongoDB, Go, RabbitMQ

Education

B.A. Mathematics - Cum Laude, Minor in Computer Science

• Mathematics GPA: 3.8, Graduated with departmental honors

• Member of Pi Mu Epsilon Mathematics Honor Society

• Programming Coursework: Machine Learning, Operating Systems, Database Engineering, Data Structures & Algorithms

• Mathematics Coursework: Regression Analysis, Operations Research, Combinatorics & Graph Theory, Probability, Real Analysis, Algebra

Projects

Novel recommendation algorithm for music based on cognitive perception

• Developed feature extraction methodology with signal processing and wavelet analysis

• Implemented basic signal processing library with Python/Numpy (filtering, convolutions, wavelet transforms)

Research collaboration developing accessibility device for augmenting human hearing

• Creating neural network architecture for understanding localization capacity of different sound signals

• Developing novel signal transformation methods to quantify and characterize human sound perception

• Utilized symbolic regression to translate engineered features into models