Growth: Starting with three top-notch engineers and an intern (and filling myself by coding in Python/GoLang), I built HiddenLayer's engineering from the scratch and designed it for highly team-cooperative personalities. It grew by 10-12x in 12 months and moved from one product to *four* in that time (unheard of for a startup). This resulted in the best engineering org that I have ever worked with. Process: I researched and established the initial pay bands for all technical positions. I created a hiring process that was optimized for speed while minimizing of staff disruption. We hit our target that any offer letter that went out should be no more than two weeks from initial interview.Patents/IP: I created a patent program that encouraged staff to invest the significant amount of work it takes to perform initial drafts and reviews of patents. HiddenLayer went from *no* successful patents to having seven critical AI patents *granted* in the next 12 months (a process that usually takes 18 months); more than dozen pending; and several more in draft at this time. This success required multiple rounds of renegotiating rejected claims and descriptions, and international filings/protections under the cooperation treaty. As it stands, not a single patent has been rejected. Additionally, I was granted three patents this period.Organizational Structure: I structured engineering into a set of product/feature teams (product engineering) and supporting teams (Developer Experience, Research Engineering). Teams were required to create charters, and document any interterm exchanges (change flow) along with stated agreements for the Definition of Done / API-Contract for each, and required separation of content updates from builds. The goal of which is to create team autonomy (that's how you scale), and direct accountability to that autonomy - all to create staff emotional investment.Lastly, Achieved SOC2 compliance in 6 months.

Ran an organization of over 125 engineers delivering endpoint security in two products: EPP (“Cylance Protect”) and EDR (“Cylance Optics”). The organization included cloud services, data lake house, and ML model updates for these products. Started a unified agent project to greatly simplify updates and deployments for both products and de-couple their release cycles - this project continued and is expected to complete in 2025Q1.I filed and was granted two patents in this position.

While Director, I was responsible for the static artifact parsers - which are both the simultaneous first step for machine learning training and the final step of in-field categorization - and the scoring engine that was embedded into Cylance Protect and OEM'd into other vendors AV engines. • Created and Ran the Parser and Engine development teams. • Created boundaries between Parser, Engine, and Product teams by establishing use of libraries and API contracts (only) as deliverables. • Guided the team to create a third, non-code-gen version of the engine that brought four-plus weeks of dev-test time at the end of release cycles down one week.I filed and was granted six patents during this position.

As Software Architect I was responsible for designing the static-artifact-deconstruction libraries, and maintaining the categorization engine that made use of them in combination with ML models to produce classifications.• Enhanced/maintained code for building Neural Network and Log-Regression Vectorizing and Classification systems • Implemented and enhanced systems to acquire intelligence as needed by Data Science and Malware Response• Designed libraries to statically deconstruct binary artifacts (PE, MachO, ELF, OLE, etc.) and create observations/features to be used both in ML training and the endpoint classification system. • Created generic interfaces (APIs) for the handling of disparate artifacts, including callbacks for handling nested artifacts.• File and Protocol level Reverse Engineering for any type of data that was examined by Cylance Protect’s AI.I filed and was granted three patents during this position.

As Sr. Developer I wrote the original implementation of Cylance' AI training code (in Java & Hadoop) a highly complex map-reduce system. • Development and Training of Artificial Intelligence and Machine Learning Systems using Java & Hadoop on AWS• My implementation brought training time for the main product's ML models down from 3-5 days to several hours - greatly accelerating the delivery-ability of Data Science and massively reducing cost.• Development of Linux and Windows Based Digital Forensics Tools using Python and Linux• Server-Side J2EE Development to add Client-Agent Management into Existing Industry Enterprise Management Console

• Member of the Rapid Integration Team for McAfee’s ePO product line specializing in integration with Intel vPro technologies as the product Deep Command. • Created a secure and enterprise-scalable OOB management system to mainboard firmware, implemented a Certificate Authority within ePO.

I managed the Western hemisphere of researchers that engage in customer emergency response. Coordinated work for our responses, responsible for short-notice decisions, and mentoring new research staff. In my first year at this position I found many problematic processes and created new systems to replace them. Key among these were :• Creating a standardized system of prioritization• Capturing tribal knowledge and documenting it• Creating processes for handing of non-standard emergency/customer events• Increasing accountability to ensure all situations have a known state and making this visible off-org.• Introduced the concept of workload metrics to the group, sufficient to project both potential bandwidth, expected latency in response, and expected time in response successfully.I filed and was granted three patents during this position.

I was responsible for handling an ever-changing series of emergencies in mobile phone/TelCo security reverse-engineered mobile phone virus and vulnerabilities, as well as competitor's products.• Rapid development and deployment of prototype products.• Solving a new problem every week, on a critical time-frame.• Architected and Deployed the AV Update System for Embedded customers. • Custom signature (DAT) sets per-platform for both mobile phones and gateways. • Live per-device and per-network entitlements enforcement. • N-Tier replication from a central server to geo-local master servers, to the public systems.• Architected and Managed the Early Warning and Response System. • Reconnaissance system of points of interest against hacker undergrounds. • Includes both automated systems and human assets (field-agents, moles, etc.). • Managed research and response for a team covering four cities on three continents.

Responsible for product architectural design, project estimation, database design, and lead programming for all projects. • Introduced a software design estimation system to Cascadia, bringing chronically over-time/over-budget schedules into check. • Designed and implemented a more universally-applicable eCommerce product and database, changing time for deployment from about 6 months to about 6 weeks for a product that includes a real-time inventory, cash-register, and customer relation management system.  • Main technologies include architecting and administrating database schemas in Oracle [8i], designing and programming Mod Perl interface, outputting data as XML, designing the more advanced XSL templates for final HTML rendering on web. • Helped administer product workload spread multiple clusters of multi-tier servers [various Linux releases]. Also was responsible for recruiting higher end technical staff.

Developed Timberline’s main product installs using InstallShield Developer 7.x/8.x and InstallShield for Windows Installer [v2].  • Produced six installs for both client and server application suites; install and set-up requirements for these products [Estimating Suite and Enterprise Estimating] were highly complex.  • Created an automated build process, that reduced a two day turn-around to four hours—cutting eight hours and allowing the addition of another four hours for smoke testing of new milestones.