· Developing complex automated data collection, aggregation, analysis, and altering systems that continuously monitor routing performance of network devices within Meta data centers worldwide.

· Leading adoption of AI-native software development using agentic harnesses such as Claude Code, with a strong focus on unit and integration testing to ensure increased development velocity and code quality.

· Led the architecture and scaling of cloud-native data systems processing 150M+ records using Python, AWS, and Kubernetes.

· Modernized IPv4 scanning infrastructure and implemented LLM/RAG solutions while mentoring the team and driving cross-functional R&D strategy.

· Engineered real-time ETL pipelines and analytics systems for hardware testing and telemetry datasets using Python, Airflow, and AWS, improving processing and reporting speeds, architecture complexity, and modularity.

· Deployed scalable interactive hardware analytics dashboards and statistical outlier detection systems for engineering teams using Plotly Dash and the ELK stack.

· Built a large-scale news and social aggregator processing terabytes of real-time data using graph algorithms, clustering, and transformer models.

· Led R&D initiatives in NLP and network science, developing specialized ML models for bot detection and conversational AI.

Taught DSCI 521: Data Analysis and Interpretation, an introductory graduate-level course in EDA and machine learning with Python.