Experience
AI Product Engineer, Agentic Edge AI and Hybrid AI
I spend one‑third of my time leading a 35‑initiative Applied AI Intellectual Property (IP) portfolio focused on Agentic, Edge and Hybrid Edge‑Cloud AI, owning its strategy, prioritization, and lifecycle as an R&D product. Key responsibilities include:
- Initiating and developing AI product concepts that can create competitive advantage, support legal defense, or generate revenue, working with a core team of 4 repeat inventors and multiple legal specialists.
- Driving the patent development process from opportunity discovery through iterative refinement, business‑case development, technical design and prototyping (e.g. Visio).
- Defining portfolio, patent, and product strategies by identifying underserved technological whitespace and novel positioning opportunities, aligning with the company's technology strategy and discontinuing IP initiatives when necessary.
- Applying Kanban-based product ownership principles to prioritize the IP backlog and manage flow across patent R&D stages, estimating key metrics including current value, unrealized value, time to market, and innovation potential.
- Creating detailed technical architectures that enable independent execution by engineering teams.
Notable outcomes
- Building this from 0-to-1, refining my understanding of disruptive strategy along the way.
- 12 USPTO patent filings (10 as first inventor, 2 as co‑inventor) and 8 internally recognized inventions.
Collectively, this work reflects applied product R&D in a Fortune 500 engineering environment.
AI Software Engineer, On-device Conversational AI Services
I spend two‑thirds of my time as a core contributor to six on-device Small Language Model (SLM) and three Automatic Speech Recognition (ASR) services in Dell's AI PC platform, which was featured as a flagship AI initiative at CES, GTC, and DTW. This work serves as a foundational capability for multiple Agentic Edge AI and Hybrid Edge‑Cloud AI initiatives. Key responsibilities include designing and implementing on-device AI inference pipelines for open-source ONNX models, enabling efficient execution across heterogeneous CPU, GPU, and NPU hardware.
Notable outcomes
- Two services were 0-to-1 developments that established the foundation for future initiatives.
- Several became either the only Dell solutions in their hardware class or the most performant at time of delivery.
- These efforts directly supported Dell's partnerships with two leading AI hardware vendors.
This work has enabled me to design and deliver production-grade AI solutions.
Software Engineer, Web Services
Built a strong foundation in .NET Web API development, GitLab CI/CD, testing, and observability. Progressed to delivering multiple microservices end-to-end, onboarding seven engineers into product teams, and collaborating with engineers and stakeholders across eight service teams.
IT Recruiter and Human Resources Member
Contributed to 15 educational projects helping students develop technical and soft skills and transition into IT roles.