At Union Pacific, I modernized large-scale, mission-critical Mechanical Systems by upgrading legacy C++ platforms, redesigning real-time data pipelines, and delivering high-availability applications used across rail operations. My work increased system performance, reliability, and operational efficiency across multiple enterprise workflows.

• Modernized core legacy systems with scalable architectures and improved real-time data handling, directly supporting mission-critical work order, inspection, and detection workflows.

• Delivered high-performance frontends that improved real-time user interaction speeds by 70%, enabling engineering and mechanical teams to make faster operational decisions.

• Overhauled enterprise Android tools with offline-first sync, edge caching, and asynchronous pipelines, cutting inspection and reporting times by 60%.

• Increased system availability by 50% by implementing structured telemetry, automated regression testing, and improved observability across multiple Mechanical Systems applications.

• Partnered with engineering, product, and field teams to deploy stable, reliable software at enterprise scale, strengthening operational efficiency across the network.

In this role, I focused on delivering and optimizing key software engineering projects for CADX Web Applications in an Agile/Scrum environment. My work enhanced both system performance and safety, while also prioritizing usability and security.

• Orchestrated production cycles and led cross-functional teams to release high-quality web apps, increasing operational efficiency by 20% and cutting post-release bugs by 15%.

• Implemented advanced UI features, server-side validations, and compliance measures, resulting in a 30% boost in scalability and a significantly improved user experience.

• Spearheaded cyber safety initiatives that delivered 99.95% availability and zero data breaches over two years.

• Mentored interns and produced comprehensive documentation, doubling onboarding efficiency and fostering a culture of growth and collaboration.

I’m building Luv Health from the ground up — a next-generation self-pay platform where patients can find hard-to-reach specialists and book appointments instantly through an AI-powered voice agent. I own the full technical strategy, system architecture, and end-to-end product execution.

• Architected and developed the entire MVP, creating a high-performance marketplace for matching patients with out-of-network doctors through a tailored, intelligent search experience.

• Integrated a Vapi-powered voice AI agent that books appointments on behalf of patients, removing phone-call friction and delivering a fast, seamless booking experience.

• Built a lightweight, relevance-driven search engine surfacing recommended doctors instantly while maintaining transparency through full search results.

• Designed the full doctor onboarding flow, enabling practices to create structured profiles, set self-pay pricing, and grow visibility outside insurance networks.

• Implemented a scalable full-stack architecture optimized for low-latency search, reliable booking workflows, and rapid iteration during MVP development.

• Led product and engineering strategy, collaborating with founders and early users to refine the self-pay model and deliver the simplest, fastest path from search → doctor → appointment.

I co-founded VortexeAI to build a next-generation agentic automation platform, enabling teams to design and deploy multi-agent workflows through a visual, developer-friendly interface. I architected the system end-to-end, from the TypeScript execution engine to the React Flow–based workflow builder.

• Designed and implemented a deterministic multi-agent orchestration engine, using graph traversal, dependency resolution, and structured validation to ensure reliable, predictable agent behavior at scale.

• Built the entire frontend architecture in React/Next.js, including the node editor, configuration panels, metadata layer, and workflow visualization, enabling intuitive creation of complex agent pipelines.

• Developed a flexible runtime for LLM tool execution and memory routing, delivering a foundation capable of supporting sophisticated automation patterns and real-world decision workflows.