I build ambitious products from first idea to production.

Problem

Create a secure and emotionally thoughtful relationship product that combines communication, memories, calls, intelligent insights, and planning without compromising privacy or mobile usability.

Decisions

Structured the platform as a couple-first relational model rather than standard broadcast-oriented feeds. Adopted end-to-end encrypted messaging, React Native with custom native bindings, NestJS, PostgreSQL, Redis, WebRTC calling networks, and structured LLM constraints for localized data integrity.

Execution

Executed across the complete development lifecycle: designed core wireframes and high-fidelity screens; coded mobile clients utilizing Expo native hooks; built backend API layers; setup signaling/TURN architectures for voice/video; developed local SQL caches for offline availability; built secure biometric locks; and automated deployments using containerized AWS services and CI/CD pipelines.

Result

Created a production-oriented product platform spanning the complete product-development lifecycle, demonstrating the ability to move between founder strategy, experience design, detailed engineering, architecture, security, delivery, and operations.

Problem

Replace the commercial Daxtra resume-parsing dependency with an internal AI-assisted candidate-ingestion platform while preserving data integrity, operational visibility, and human oversight. The project required moving away from high per-parse vendor licensing costs and eliminating third-party lock-in.

Leadership Context

Managed five software developers and led the focused one-month delivery of an AI-assisted candidate-ingestion platform that replaced Daxtra. The system automated candidate ingestion into Mercury CRM and PostgreSQL while preserving data integrity with confidence-scored human-in-the-loop reviews.

Decisions & Execution

Designed an asynchronous pipeline where files (PDF, DOCX, DOC, RTF) are extracted and read. Used custom pre-processing OCR models for image scans. Implemented structured OpenAI schema outputs validated against database schemas. Introduced confidence metrics that trigger routing flags to a unified Salesforce/Mercury CRM human review panel.

Result

Directed the replacement of a commercial resume-parsing vendor with an in-house AI platform that processed approximately 2,500 distinct resumes and attachments during its first four production weeks, achieving approximately 96% final-state success and 86% straight-through automation.

Problem

Support global digital career transformation platforms requiring unified applications (KF One), Assessment Analytics tools, high concurrent scalability, and modern automated CI/CD practices across global cross-functional scrum teams.

Decisions

Selected cloud-agnostic architectures (supportable across Azure, AWS, PCF) and centralized data warehousing to consolidate analytics across distinct candidate platforms. Pushed the early adoption of AI-augmented engineering workflows (Cursor, custom MCP servers) to solve performance bottlenecks and speed up local feature rollouts.

Leadership Scope

Managed more than 25 team members across global software-delivery teams while continuing to guide architecture, engineering practices, Agile execution, and AI-assisted development adoption.

Key Outcomes

• AI-Driven Efficiency: Improved developer efficiency by approximately 42% through AI-assisted engineering workflows across multiple engineering divisions.
• Scalable SaaS Platform: Architected and delivered an enterprise career-platform designed to support more than one million concurrent users (career assessments, path mapping, and skill building).
• Multi-Scrum Leadership: Guided three global engineering teams in delivery of KF Intelligence Cloud and Career for Technology (KFCT) Teams application on schedule.
• Analytics Engine: Oversaw multiple feature deliveries for the Assessment Analytics platform, serving over 500 enterprise clients.