Embedded Engineering Leader
for High-Growth Startups
I partner with a select group of founders at the moments that define what a company becomes. Not as an advisor across a table — embedded inside the team, owning the architecture, building the IP, and making the technical bets that determine whether a venture is fundable, defensible, and built to last.
Embedded Engineering Partner
I embed inside high-growth startups as an engineering leader and partner — bridging the gap between ambitious product ideas and scalable, production-grade delivery. Not advisory. Not fractional. Fully inside the team.
Embedded at Critical Inflections
Advisory and fractional models fail founders at inflection points because the depth required spans every technical function simultaneously. I embed inside the founding team — architecting the IP, writing critical-path code, building the engineering organization — with co-founder accountability, not consultant distance.
- Architect Initial IP
- Critical-Path Code
- Founding Team Recruitment
Systems Where Failure Is Not An Option
I specialize in domains where off-the-shelf AI is insufficient: precision agriculture, enterprise compliance, geospatial intelligence. Stakes that justify rigorous engineering and where the gap between a prototype and production-grade is where most technical partnerships fail.
- Mission-Critical Reliability
- Regulatory Compliance
- Real-World Constraints
R&D to Scalable IP
Converting complex research into defensible, investable intellectual property. I architect systems designed for patents, competitive moats, and long-term enterprise value — not demos, not proofs of concept.
- Patent-Ready Architecture
- Competitive Moats
- Enterprise-Grade Systems
Technical Organization Building
Beyond code: building the engineering culture, hiring the founding team, establishing the processes that let organizations scale without losing velocity or accumulating technical debt. The infrastructure that outlasts any individual contributor.
- Engineering Culture
- Hiring & Onboarding
- Scalable Processes
Where Rigor Meets Frontier Technology
I spent a decade in safety-critical robotics — designing autopilots under DO-178C certification, managing autonomous systems where failure had real, physical consequences. That background instilled a standard of engineering rigour that transfers directly to AI: the gap between a working demo and a production-grade system is exactly where most AI initiatives stall. Today I build the infrastructure layer for AI-native companies: agentic systems operating at enterprise scale, geospatial ML platforms processing planetary data, multi-agent frameworks in domains where off-the-shelf AI is insufficient. Most technical partners have either operational rigour or frontier AI depth. Operating at both simultaneously — and with co-founder accountability rather than advisory distance — is what I bring to the companies I work with at critical inflections.
Aerospace-Grade Rigor
A decade designing autopilot systems under DO-178C certification. I bring safety-critical engineering standards to AI products, where the gap between a working prototype and a production-grade system is where most technical bets fail.
Physical World Expertise
From neural SLAM algorithms on autonomous drones to sensor networks in the Namibian bush. I understand the friction between code and the real world that most AI engineers never encounter — and that separates durable systems from demos.
AI-Native Architecture
Agentic systems replacing enterprise back-office workflows, geospatial ML platforms at planetary scale, multi-agent frameworks for high-stakes domains. I build AI infrastructure that operates where off-the-shelf solutions are insufficient.
Engineering Culture Builder
Scaling organizations that balance rapid experimentation with long-term architectural sanity. I recruit founding engineering teams and build cultures that ship without accumulating debt — the infrastructure that outlasts any sprint.
I partner with a select group of founders at the moments that define whether a company accelerates or stalls.
Where the CEO needs a co-equal technical partner — not an advisor, not a hire — embedded at the same depth on the product and engineering layer.