AI Content Designer
Model Alignment & Human-Centered Design Systems
12+ years at Google training AI models and designing content systems at scale. Now building Veracitas: practical AI tools grounded in truth, clarity, and human voice.
The Journey
At Google, I worked across multiple product areas as a systems-level content designer: Travel, Transactions, Food, Entertainment, and Search.
I created Content Principles for Search's Real World Content team, which guided content strategy for the Search Generative Experience. I trained SGE models and contributed to early Gemini model development.
I led DSA content implementation, balancing regulatory compliance with product velocity, making pragmatic content decisions that satisfied legal requirements while keeping launches on track. I built the Local Services taxonomy that now classifies millions of businesses globally.
I operated at the intersection of product, legal, engineering, and policy—the kind of cross-functional systems work that's rare at Staff level but critical at scale.
After 12 years, I was ready for my next chapter. I'd been planning my departure and had started exploring other opportunities.
When I left Google, I decided to build something I couldn't develop there: end-to-end product ownership. I founded Veracitas to do exactly that.
BIBIS—a complete AI-orchestrated content system built in 2 months—is the result. It proves I can own full product cycles while maintaining Google-level rigor.
I'm now seeking my next full-time role where I can bring both: systems expertise at scale and the full-cycle ownership I've since developed.
How I Work
Truth Over Hype
Clarity is the baseline, not an aspiration. I cut through noise to find what actually matters.
Systems Thinking
Frameworks that scale without losing coherence. Even Canva's algorithm noticed: Top 5% for brand consistency across 109 designs in 35 days—after learning the tool from scratch while building BIBIS. When you build with systems thinking from Day 1, even AI notices the pattern.
Human-Centered Voice
Technology should make complicated things feel clear, not make simple things feel complicated.
Projects
Designing a Service Classification System at Global Scale
Building taxonomy infrastructure for millions of businesses across multiple Google products.
- Reference example in Google's internal glossary for taxonomy
- Unified classification across Search, Maps, and Ads
- System classifies millions of service businesses globally
- Framework continues to scale as Local Services expands
Information architecture • Systems thinking • Cross-product leadership
Content Principles for AI-Generated Search Results
Defining trust and clarity standards for LLM outputs at Google scale
- Principles adopted as foundational framework for SGE real-world content
- Guided model behavior for billions of search queries
- Contributed to trust and safety standards
Model alignment • Content strategy • AI safety design
* Additional details available upon request (NDA restrictions apply).
Building an AI-First Content System from Scratch
Google-scale rigor. Founder-speed execution.
- Complete product in 2 months solo: strategy, research, design, AI orchestration, launch
- Multi-platform AI architecture with guardrails and quality control
- Vertically-adaptable system serving diverse users through inclusive design
Multi-Platform Orchestration
Strategic Product Architecture
User-Centered Iteration
Product strategy • Systems architecture • AI orchestration • End-to-end ownership
Translating System Failures for Non-Technical Audiences
Identifying design traps and hidden operational risks in software systems before they become problems businesses can't easily undo.
- Identified patterns where 80/20 product optimization creates critical failures for edge-case users
- Analyzed systemic gaps in platform design that assume organizational resources small businesses lack
- Documented real-world cases, including credential governance failures and support infrastructure gaps
Systems analysis • Technical translation • Risk assessment frameworks
About
I founded Veracitas because I believe AI and UX need more truth and less noise.
My work—whether at Google scale or helping small businesses—centers on one question: How do we make complex technology feel human?
I'm actively seeking my next full-time role in AI content design, model alignment, or systems-level UX. I'm particularly interested in companies working on AI safety, model alignment, and human-centered AI design; places where building technology responsibly is core to the mission, not an afterthought.
While I continue to build Veracitas products, my primary focus is finding the right full-time position where I can bring both Google-scale systems expertise and the end-to-end ownership I've subsequently developed.