Fractional CTO
CTO-Level Engineering Leadership, Augmented by Agents
You get senior architecture decisions, engineering strategy, and shipped code — augmented by AI agents that extend what one person can deliver. At a fraction of the cost of a full-time hire.
Built for funded teams shipping AI into production.
The problem
The Problem
You need engineering leadership. The usual options each come with a real cost.
The full-time hire
Hiring a full-time CTO takes 3-4 months and costs $250K+/year plus equity. Your backlog grows while you search.
The consultancy
Consultancies charge $150-200/hour with unpredictable monthly spend and no skin in the game.
The go-it-alone build
Your team ships an AI feature that works in staging and falls apart with real users. That's a judgment gap, not a tooling gap — knowing what to verify, what not to trust, and what breaks once the happy path ends.
The model
The Model
I provide CTO-level engineering leadership — architecture, strategy, code review, technical direction. AI agents handle the mechanical work: scaffolding, tests, refactoring, documentation. I review every change.
You get staff-level decisions and shipped code, faster than a hire and cheaper than a consultancy. The agents extend what I can deliver, not replace judgment with output.
The word that matters is augmented. Agents get me more done in a day — they don't do junior work on the side. Every decision, every tradeoff, every merged change goes through my judgment.
The background
The Background
- Engineering team scaled as CTO at Buoy Software
- 0 → 50+
- Engineering team scaled as CTO at Buoy Software
- Cleared medical device software shipped — 510(k) BK231004
- FDA
- Cleared medical device software shipped — 510(k) BK231004
- Building production software under real constraints
- 15+ yrs
- Building production software under real constraints
I was CTO at Buoy Software, where I grew the engineering team from 0 to 50+ and shipped FDA-cleared medical device software. The discipline that gets software through FDA clearance — knowing what to verify, what to prove, and what breaks under real use — is the same discipline that gets AI features past the demo.
Today I build production AI systems daily and publish the workflows, evals, and failures in public. You can check the work before we ever talk.
Comparison
How It Compares
| Option | Monthly Cost | First Delivery | Commitment |
|---|---|---|---|
| Full-time CTO | $20K+ + equity | 3-4 months | 12+ months |
| Consultancy | $15-25K (variable) | 2-4 weeks | Project lock-in |
| Damian — Fractional CTO | $15K–$60K/month | 1-2 weeks | Month-to-month |
Most engagements start with a 2-week Foundation Sprint at $12K flat — a smaller commitment that validates fit on both sides before either of us signs up for a retainer.
Scope
What's Included
- Architecture decisions and technical direction
- Code review and quality standards
- Engineering strategy and roadmap input
- Shipped code — features, fixes, hardening
- AI stack evaluation and consolidation (cost controls, tool selection)
- Team workflow review (PR process, CI/CD, deploy pipeline)
- Weekly sync calls to adjust priorities
Fit
Who This Is For
Good fit
- Funded engineering teams (seed–Series B) that need senior judgment but can't justify a full-time CTO
- Technical founders making architecture decisions alone
- Teams whose AI stack grew organically and needs hardening, evals, and observability
- Regulated/high-stakes environments where AI has to actually work
Not a fit
- Teams wanting extra hands to grind tickets
- "Add AI to everything" consulting
- Projects without clear user value
- Pre-seed teams without budget for senior engagement
Process
How It Works
- 01
Intro call
30 min
Understand your stack, team, and what's blocking you.
- 02
Foundation Sprint
2 weeks • $12K flat
Architectural assessment + one shipped piece. Paid trial for both sides.
- 03
Ongoing retainer
$15K–$60K/month
Direction reset every two weeks, 30-day notice.
For context: most solo fractional CTO retainers cluster around $5K–$15K/month. This range sits above that because the engagement includes shipped, reviewed implementation — not advisory hours alone. That's what the agents change about the economics.
From the clients
What Clients Say
“I found Damian via Claude when looking for a real software engineer to take an application from vibe-coded internal demo/prototype to fully deployed tool in less than 3 weeks…
What I was looking for was just someone to make sure PII was secure, that we didn't have any glaring security vulnerabilities in our code and database, and to make sure the app wouldn't break when being used in real life. He turned out to be a true strategic partner who not only brought proper DevOps to that app and every other project we are working on at WareSpace, but also helped define the product direction, scope, roadmap, etc. through consultative working sessions. It's rare to find an engineer with deep technical knowledge, strong business acumen, and who also speaks "human" to communicate with non-technical stakeholders.”
Eric Golman
CMO, WareSpace
FAQ
Frequently Asked Questions
What's your background as a CTO?
I was CTO at Buoy Software, where I grew the engineering team from 0 to 50+ and shipped FDA-cleared medical device software (510(k) BK231004). Before and since: 15+ years building production software, including regulated environments, and daily hands-on work shipping AI systems into production.
How is this different from staff augmentation?
Staff augmentation gives you more hands. This gives you engineering leadership that owns technical direction, augmented by agents to ship faster. You get judgment and output, not just output.
How do agents fit in?
Agents handle the mechanical parts of engineering: scaffolding, tests, refactoring, documentation. I review every change. The agents extend what I can deliver in a week, but every decision goes through my judgment.
What if we already have a CTO?
I work alongside your existing CTO as a force multiplier, not a replacement — second opinion on hard calls, help sorting out which AI tools are worth keeping, and hands-on coding when you need it.
Do we need to be using AI tools already?
No. Part of the engagement is helping you adopt the right AI tooling for your team and codebase.
What does the Foundation Sprint produce?
A written architectural assessment and one shipped foundation piece: eval framework, conventions doc, migration plan, or rollout playbook.
Get Engineering Leadership That Ships
Book a free 30-minute intro call. We'll look at your stack, your team, and what's blocking you — and I'll tell you honestly whether this is the right fit.
No pitch. No pressure. Just a conversation about your engineering.