The operator who connects strategy to execution
Most organizations have business leaders on one side and technologists on the other. I build and lead the teams, systems, and processes that connect them. I've built customer-facing organizations from scratch and scaled revenue from $30M to $100M+ ARR. I scale through talented people, and now amplify that with AI.
The business foundation
20+ years of building, hiring, and leading customer-facing organizations. This is what gives everything else context and direction — I know how to scale through people because I've done it repeatedly.
Building from 0→1 (and scaling it)
Built Sales, Pre-Sales, and Customer Success from zero at OceanX. Scaled to $100M+ ARR. Defined roles, hired teams, set standards, created the operating rhythms.
Leading people through change
Highest manager score company-wide at Guthy|Renker. Led post-acquisition integration at Tribune. 50+ FTEs plus offshore teams. I know how to bring people along — not just deploy technology at them.
Technical credibility
BS Engineering (USC). Architected cloud-native SaaS platform (AWS, PCI L1). Led technical integrations, API implementations, architecture reviews. I can sit in a room with engineers and add value.
Customer-facing + strategic
Enterprise discovery, pre-sales scoping, C-level negotiations, strategic account management. Translate customer needs into product direction and protect the team from chaos.
What I mean by "business architect"
I'm not a low-level code architect. I operate at the system level — seeing how business objectives, organizational dynamics, technology capabilities, and customer needs connect, then building the team and designing the plan that delivers. Think of it as the macro architecture of getting things done across people, process, and technology. Sometimes that means I'm hiring the first 10 people and defining roles. Sometimes it means leading 50+ across multiple functions. And sometimes — especially now — it means orchestrating a mix of human teams and AI agents toward the same objective.
What I bring to the table
- Map the ecosystem and ask the right questions before building
- Design plans that balance ambition with what's actually achievable
- Hire, develop, and lead high-performing teams to execute
- Orchestrate across teams, AI tools, and stakeholders
- Set quality bars — coverage, security, usability, trade-offs
- Navigate the human side: inertia, politics, fear of AI, org change
What I don't claim to be
- A senior software engineer writing production code all day
- A data scientist building models from scratch
- Someone who needs to be — there's a clear and growing trend towards managing agent teams, not lines of code
AI as an accelerant
I completed Stanford's AI Professional Program — four graduate-level certificates in ML, NLP, and Computer Vision. But the real value isn't the credentials. It's that I understand the technology well enough to know what's possible, what's hype, and how to apply it to real business problems.
I build with AI tools the same way the best operators work today: define the objective, architect the approach, orchestrate execution with AI agents and workflows, review the output, and iterate. I'm technically fluent enough to evaluate trade-offs, ask the right questions, and ensure quality — without pretending I need to write every line myself.
What this looks like in practice
- Built multiple production websites using AI-augmented development (Claude Code CLI)
- Designed and built RAG systems, ML pipelines, and multi-agent prototypes
- Write analytical briefs that synthesize complex AI/business topics into clear, actionable insights
- Evaluate AI architectures — chunking strategies, retrieval approaches, model selection, security considerations
Why this combination is rare
People with deep business experience rarely invest in serious AI/ML education. People with AI skills rarely have 20 years of enterprise leadership and org-building. And almost nobody in either camp has actually built and led large teams through the kind of organizational change that AI adoption demands — the inertia, the politics, the fear of displacement, the gap between what technology can do and what people are ready to accept.
I've led organizations through exactly the kind of hard change that AI adoption demands — post-acquisition integrations, building functions from zero, scaling teams through ambiguity and resistance. 50+ person organizations, highest manager score company-wide, a track record of creating environments where strong people do their best work. That foundation — combined with real AI technical fluency and the ability to build trust through uncertainty — is what positions me to lead this next wave.
What I'm looking for
Roles where I can apply the full stack — business architecture, technical fluency, AI capability, and people leadership. GTM, Solutions, or AI-enabled leadership positions where the job is to build and deliver solutions that are high impact.
California-based or fully remote. Also open to interim or fractional engagements.