Fractional CTO and end-to-end product leadership
What I take on: end-to-end ownership of a product and the team building it, roadmap, hiring, delivery cadence and the architecture underneath, as the one person accountable for the outcome.
I have spent 12 years on both sides of a product: building it, running the team that builds it, and keeping the infrastructure under it upright. Most engagements start because a founder or a team needs one person who owns delivery end to end, not someone executing a backlog somebody else wrote.
What does end-to-end product and technical leadership look like?
It looks like owning the roadmap, the stakeholders and the team, not just the code. In my current role I run sprint planning, stakeholder management and code review across multiple engineering squads, work that lifted on-time delivery to 95% and cut production defects by 30%.
Before that I led a cross-functional team of 20 developers, designers and marketers across five concurrent startup projects. I owned the hiring pipeline, ran 1:1s and mentorship, and handled performance management, the part of leadership that never shows up in a commit log. I also wrote the engineering rulebook the team worked from, AGENTS.md, standardising code quality across five products instead of leaving each one to drift on its own.
Product ownership starts earlier than delivery, too. I won a client by writing the technical proposal myself, then led delivery on it, and on a pharmaceutical-industry engagement I owned client onboarding end to end, including running the client meetings, rather than handing that off to a PM.
I mentor junior engineers directly on backend architecture, database design and testing: the same leadership work, at a smaller radius.
Evidence: the case studies and the full record on the about page.
DevSecOps and platform architecture
The leadership above sits on top of infrastructure I build and run myself. I take infrastructure that grew by accident and give it a shape someone else can operate: Terraform for anything that has to be reproducible, Kubernetes only where the workload earns it, and scanning wired into CI so a vulnerability fails a build instead of waiting for a quarterly report.
The clearest example is an EdTech platform I moved off AWS onto self-hosted managed cloud, with nginx in front of the apps. I owned every server, the infrastructure and the security posture single handed, through the migration and after it. Infrastructure cost fell by roughly 70%, with zero downtime.
Hybrid on-prem and cloud infrastructure I architected has held 99.95% uptime, with monthly cloud spend down 45% and 80% of critical vulnerabilities closed inside the first two quarters of hardening. The vulnerability number came from putting the scanners in the pipeline rather than in a report nobody reads.
Evidence: the case studies and the full record on the about page.
Self-hosted AI systems and integrations
Production language models on hardware you control. I have fine-tuned self-hosted models (GPT-OSS, Llama, Qwen) behind a custom chat and evaluation engine for a pharmaceutical-industry client, owning that one from the proposal through to production, and built a document OCR pipeline on the Claude API for an EdTech platform that evaluates college offers and financial-aid packages.
The evaluation engine matters more than the model. Picking a checkpoint with no way to measure whether it actually improved is how a team ends up with an expensive system nobody trusts, and it is the step most projects skip.
Both engagements are described by industry rather than by name because the work is under NDA.
Evidence: the case studies and the full record on the about page.
How does an engagement start?
Email [email protected] with what is breaking, or with what you are trying to ship and cannot. A short description of the stack and the deadline is enough for me to tell you whether I am the right person, and what I would look at first.
Remote, with full working-hours overlap for the US, UK and EU.