Staff Software Engineer · Austin, TX
ML Systems · MLOps · Cloud & Big Data · Generative AI
I build machine-learning systems for regulated, cloud-scale data platforms — privacy & compliance automation, hyperscale cost optimization, and generative-AI operations on AWS and Snowflake. 6+ years across AWS, RR Donnelley, and research labs.
I'm a Staff Software Engineer at RR Donnelley, where I lead ML/MLOps, Snowflake & AWS data platforms, compliance automation, and LLM usage analytics. Previously I was a Software Development Engineer at Amazon Web Services, building serverless, high-throughput streaming systems.
My work sits at the intersection of cloud-native ML, big-data engineering, privacy engineering, and generative AI — applied across security, healthcare, agriculture, and marketing. I hold an MS in Computer Science from the University of Missouri (GPA 3.9), have authored five peer-reviewed publications, and have been recognized with my company's Diamond Award and a company hackathon win for a neuromorphic attribution system.
Outside of shipping systems, I serve as a conference judge, journal guest editor, and peer reviewer, and I mentor high-school students in STEM.
Production systems and original contributions with measurable impact.
Spark-based architecture that automates "right to be forgotten" requests across 50 TB of S3 data — turning weeks of manual effort into hours while guaranteeing regulatory compliance. Featured in technology media for its scale and approach.
Designed S3 lifecycle policies and storage-tiering architecture that reduced storage costs by $120,000 annually, alongside Spark refactors that cut SageMaker infrastructure spend by 40%.
Company Hackathon Winner (2025). A real-time marketing-attribution system that pairs neuromorphic (spiking neural network) computing with causal inference — a novel application of brain-inspired computing to business intelligence.
Serverless architecture using SQS and Lambda to capture LLM API usage at high velocity, enabling granular, per-team cost analysis and governance of generative-AI spend.
At AWS, designed serverless applications with Lambda, Kinesis, SQS, and SNS to process real-time data at ~4,000 records/second, with SLOs/SLAs and on-call ownership.
Peer-reviewed research across security, cloud, healthcare, and agriculture.
BDAA 2025 · Oral presentation
Eight meta-learning ensemble SVM models with a Focused-Minority ensemble; recognized by reviewers as a "novel meta-learning ensemble approach."
IJIRSS · 2025
Up to 90% network communication cost savings via dynamic provisioning; 34% performance optimization and 40% reduction in hardware replacement costs.
AMIA Clinical Informatics Conference · 2022 · First-prize poster
Time-Gated LSTM on the 40,000+ patient MIMIC-IV dataset, outperforming baselines for early acute-kidney-injury prediction.
IEEE SSCI · 2021
SVM ensemble reached 83.8% test accuracy (+7% over single SVM); USDA NRCS–acknowledged, cited internationally.
IEEE · 2020 · 30+ international citations
Combined CNN-LSTM architecture reaching 99.6% training accuracy on NSL-KDD, cited by institutions across 8+ countries.
Feature on the Spark-based 50 TB privacy-compliance platform that turns weeks of manual deletion into automated hours.
Read article →Quoted as a staff software engineer on practical use of AI coding assistants — Gemini CLI and GitHub Copilot — in production workflows.
Read article →Featured among industry experts on practical ways AI transforms financial strategy and cloud cost decisions.
Read article →How AI is evolving from passive tools into autonomous collaborators — orchestrating multi-agent systems with CrewAI and standardized tooling via the Model Context Protocol (MCP).
Community talk on building production-grade, agentic AI workflows in Python.
by Andrea Bonime-Blanc
by Patrick Bangert
by Catt Small
RR Donnelley NXTDRIVE™ Data Science Team
Neuromorphic real-time attribution
Top 10 of 300, ABV-IIITM
AMIA / UNT research showcase
Improving Undergraduate STEM Education (IUSE)
5th IEOM India International Conference
IEOM African (6th) & GCC (3rd) Conferences
Springer — ICT for Global Innovations & Solutions
BDAA 2025 International Conference, Innsbruck
Business Intelligence Group & Herizon Awards
Intl. Journal of Distributed Computing & Technology
IEEE Transactions on Professional Communication
iCouldBe e-mentoring program
Swachh Bharat Summer Internship
I'm always open to interesting problems in ML systems, cloud data platforms, and applied AI. Reach out and I'll get back to you.