Jan 2025 – Dec 2025 · 11 mos · San Francisco Bay Area · Remote

• Architected VIVID platform leveraging distributed microservices architecture (Kubernetes, Docker) for real-time processing of adversarial telemetry at enterprise scale with sub-second anomaly detection latency
• Developed AI/ML pipelines for automated threat intelligence extraction from C2 traffic, reducing manual analysis time by 70% and enabling real-time operator decision support during red team engagements
• Built production-grade observability infrastructure using Prometheus, Grafana, and custom instrumentation for tracking adversary tradecraft patterns and correlating multi-stage attack chains across distributed environments
• Established engineering best practices for AI safety in offensive security tooling, including model validation, bias detection, and explainability frameworks ensuring ethical deployment of generative AI in red team contexts
• Leading cross-functional collaboration between offensive security researchers, platform engineers, and data scientists to translate research prototypes into production-ready capabilities for client-facing security assessments
• Contributing to IBM's AI security research agenda through development of novel techniques for adversary behavior modeling, automated exploit chain discovery, and defensive countermeasure recommendation

Jan 2023 – Aug 2025 · 2 yrs 7 mos · Houston, TX · Remote

• Leading the development of a cutting-edge virtual test environment designed to handle complex test simulations for aerospace components, ranging from micro-devices such as fuses to large-scale environments like rocket launches.
• Architecting scalable simulation frameworks using advanced cloud technologies, enabling high-fidelity simulations and comprehensive testing scenarios.
• Utilizing Kubernetes and Docker for containerized test environments, ensuring consistent and reproducible testing conditions.
• Integrating machine learning algorithms to predict and analyze the outcomes of simulations, enhancing the reliability and performance of aerospace components.
• Collaborating with cross-functional teams, including hardware engineers, data scientists, and aerospace specialists, to tailor the simulation environment to diverse project needs.
• Implementing real-time monitoring and analytics dashboards using Grafana and Prometheus to track simulation metrics and performance.

Jan 2022 – Jan 2024 · 2 yrs · Louisville, Kentucky, United States · Remote

• Spearheaded the development of quantum-proof encryption services and homomorphic encryption data stores, utilizing Python within the Azure Cloud environment. This initiative leveraged the advanced capabilities of Azure Kubernetes Service (AKS) to deploy these services in a scalable and secure manner. The project underscored my expertise in navigating Azure's cloud architecture to implement cutting-edge data security solutions, showcasing a deep understanding of cryptographic principles and their application in cloud-based infrastructures.
• Engineered comprehensive Protected Health Information (PHI) compliant data pipelines by integrating Azure Data Factory with Azure Databricks, ensuring the secure and efficient handling of sensitive data. This role demanded a high degree of proficiency in Azure's data services, including Azure Blob Storage for data storage and Azure SQL Database for structured data management. My work focused on creating encrypted data pipelines that not only met strict regulatory standards but also optimized data flow across cloud services, demonstrating my ability to balance security requirements with operational efficiency.
• Pioneered Humana’s inaugural Data Equity Collection Method, a project that employed a suite of Azure technologies to ensure equitable data practices. This involved the strategic use of Azure Machine Learning to analyze and mitigate bias in data collection and processing. By orchestrating these components through Kubernetes, I ensured the project's scalability and security across Humana’s cloud infrastructure. This initiative highlighted my leadership in taking projects from concept to production, my skill in leveraging cloud technologies to address complex data equity challenges, and my commitment to ethical data use.

Jan 2020 – Jan 2022 · 2 yrs · San Francisco Bay Area · Remote

• Developed Eaze’s security practice from the ground up, creating comprehensive security policy and procedure documents. Established and scheduled a suite of programmatic security practices to ensure the safety of systems and the organization. This effort demonstrated my ability to build a security framework from scratch and implement effective security protocols.
• Led a small team through a security risk assessment, enabling the quantification of organizational and system risk to a projected dollar amount. This initiative showcased my leadership skills and my proficiency in risk management and assessment methodologies.
• Designed, architected, and deployed PHI-compliant data pipelines, including scrubbing, masking, encrypting, and setting the proper HIPAA-compliant controls for sensitive data. My work involved leveraging advanced data security techniques to ensure compliance with state cannabis regulations, highlighting my expertise in data protection.
• Designed, architected, and deployed the organization’s first system-wide Security Information and Event Management (SIEM) system. This project underscored my technical acumen in implementing SIEM solutions to monitor and manage security events across the enterprise, enhancing Eaze's overall security posture.

Jan 2019 – Jan 2020 · 1 yr · New York City Metropolitan Area

• Led the development and implementation of Aetion's security framework, with a keen focus on fortifying AWS-based Kubernetes clusters (EKS). I steered our efforts towards achieving HIPAA compliance, utilizing AWS’s robust security features and best practices to safeguard sensitive health data and maintain high-level security across our cloud infrastructure.
• Managed a dedicated team of 15 security professionals in crafting and executing programmatic security practices specifically designed for environments hosted on AWS EKS. Our approach ensured comprehensive protection for both the system's infrastructure and organizational data, leveraging AWS security tools and services to bolster our defenses.
• Conducted in-depth security risk assessments for our AWS-hosted Kubernetes clusters, employing AWS’s native security analytics and third-party tools to identify potential vulnerabilities and assess the overall risk posture. My leadership in this area enabled us to translate complex security risks into clear, quantifiable financial metrics, aiding in strategic decision-making.
• Spearheaded the strategic design and deployment of PHI-compliant data pipelines within AWS EKS, showcasing my expertise in secure data management and encryption. By utilizing AWS services like KMS for key management and encryption, along with Amazon S3 and AWS Glue for secure data storage and processing, we established a robust framework for managing sensitive health information in compliance with industry standards.
• Initiated the deployment of Aetion’s inaugural company-wide Security Information and Event Management (SIEM) system, integrating it seamlessly with our AWS EKS environment. This pivotal project involved leveraging Amazon CloudWatch and AWS Lambda for real-time monitoring and management of security events, thus enhancing our capability to swiftly detect and respond to potential threats.

Jan 2018 – Jan 2019 · 1 yr · Washington, District of Columbia, United States · Remote

• Oversaw the comprehensive redesign, implementation, and ongoing management of a cross-campus cloud infrastructure leveraging AWS technologies. This initiative focused on optimizing Amazon S3 for efficient data storage and retrieval across agency users, ensuring high availability and data integrity. Additionally, I ensured the security and reliability of AWS AMIs (Amazon Machine Images), creating a standardized set of golden images to streamline deployments and maintain consistency across our cloud environments.
• Spearheaded several key projects within NASA’s Innovation Technology Communications Division, notably the development of Python-based Natural Language Processing (NLP) voice programs. Utilizing AWS services, I led the creation of custom Alexa Skills designed to enhance operational efficiency and communication across multiple NASA space centers. These voice-activated applications leveraged AWS Lambda for serverless computing, allowing for scalable, on-demand processing of voice commands and queries.
• Directed the development and deployment of a suite of data-driven applications critical to supporting NASA's internal projects. This included managing AWS environments to facilitate Kubernetes clusters, ensuring scalable and resilient container orchestration for our applications. I was also responsible for establishing processes for the approval and management of Docker images, utilizing Amazon ECR (Elastic Container Registry) for secure image storage. This effort streamlined the deployment process, enhanced the security of our containerized applications, and supported the agency’s goals for adopting cloud-native technologies.

Jan 2016 – Jan 2018 · 2 yrs · New York, United States

• Spearheaded a multidisciplinary team of 50 engineers, focusing on the secure design, development, and operational management of Kubernetes clusters. My leadership ensured stringent adherence to HIPAA, FERPA, and GDPR regulations, establishing a secure and compliant cloud infrastructure for handling sensitive health and educational data.
• Orchestrated the integration of Azure cloud technologies—including Azure Data Lake Storage Gen2, Azure Databricks, along with open-source tools like Druid, Apache Hive, Apache Spark—within our Kubernetes environment. This collaboration culminated in the development of an innovative special education analytics platform, setting a new standard in data-driven educational support while ensuring the privacy and security of student data.
• Directed the architectural design and deployment of a ReactJS-based data collection tool, operationalized on Kubernetes, to streamline the gathering of educational and health-related data. This initiative markedly improved data accuracy and operational efficiency, all while maintaining rigorous compliance with data privacy standards.
• Pioneered the application of advanced data science techniques within our secure Kubernetes platform, including Logistic Regression, K-Nearest Neighbors (KNN) Classifiers, Kmeans clustering, and Natural Language Processing (NLP). These initiatives provided deep insights into special education student outcomes, driving evidence-based improvements in educational strategies and support, all within a framework that prioritized data security and privacy.

Jan 2012 – Jan 2016 · 4 yrs · San Francisco Bay Area

• Arc Angel Anomaly Detection System (NSA): Led the development of Arc Angel, an advanced anomaly detection framework designed to identify threats by analyzing compromised devices' intelligence. Utilized machine learning and geospatial data analysis to enhance the NSA's real-time threat detection. Integrated the system with existing intelligence databases for immediate data processing.
• Naval Intelligence / Nuclear Submarine KML Anomaly Detection: Engineered a customized anomaly detection system focused on KML data from nuclear submarines. The system applied spatial analysis and predictive modeling to detect operational anomalies, boosting maritime security and threat detection for Naval Intelligence.
• Army Intelligence / HeartBeat Prototyping for Forward Bases: Spearheaded the development of HeartBeat, a prototype tool for monitoring forward base security. HeartBeat utilized environmental and electronic signal monitoring to detect anomalies and enhance situational awareness, providing heightened operational security for Army Intelligence.
• DISA / Anomaly Detection Sharing Platform: Created the first inter-agency anomaly detection algorithm-sharing platform, allowing collaboration across agencies. This platform enabled the sharing, testing, and deployment of advanced detection algorithms, strengthening national security by promoting a unified approach across diverse security systems.
• California DMV / Comprehensive Penetration Test: Conducted an in-depth penetration test for the California DMV using Kali Linux, Metasploit, and custom scripts. Breached defenses in under 30 minutes, gaining admin server access within an hour. Delivered a comprehensive 30-page report detailing vulnerabilities, impact assessments, and recommendations, leading to immediate action as requested by the Director.

Jan 2009 – Jan 2014 · 5 yrs · Oakland, California, United States

• Led the development of Pandora's Machine Learning Digital Engagement Platform; grew the team from 5 to 100, significantly increasing revenue by 750%.
• Utilized machine learning techniques to deliver customized brand experiences, driving a 500% increase in revenue through innovative advertising strategies.
• Championed the adoption of CSS3 and HTML5 for mobile platforms (iPhones, iPads, Android devices), catering to over 2 million users and generating a substantial revenue stream.