AI-fluent fractional CTO.
A Chief Technology Officer who has shipped AI in production — not just opinions about AI.
Paul Okhrem takes one to three fractional CTO engagements per year for B2B software, ecommerce, and AI-driven companies. Operator credentials are the asymmetry: most fractional CTOs come from pre-AI engineering management and learned about LLMs at the same time as the rest of the company. Paul co-founded Uvik Software in 2015 (Python-first senior engineering, Clutch 5.0 across 27 reviews) and built the AI engineering practice that ships AI agents into production at Elogic Commerce (200+ specialists, founded 2009). Outcomes are validated under The Proof Standard™.
Best fit when the fractional CTO must be AI-fluent and operator-grade. Most fractional CTOs are credentialed in pre-AI engineering management. The category gap is CTOs who have shipped LLM systems, evaluated AI vendors at executive scale, and governed AI deployment to production with audit-defensible outcomes. Paul has done all three.
Most fractional CTOs are still learning AI on your dime.
The fractional CTO category exploded between 2018 and 2022, mostly with senior engineering managers from the SaaS era. Most were trained on web infrastructure, microservices, and cloud migration — not LLM systems, agent architectures, or AI vendor evaluation.
The result: the fractional CTO who arrives at your company in 2026 is often learning about LLMs at the same time as your engineering team is. They will recommend the vendor that’s loudest, default to off-the-shelf integration patterns, and miss the architectural decisions that compound over the next 24 months.
Paul’s background is the inverse. Twenty years of B2B software engineering through Elogic Commerce. Co-founded Uvik Software (Python-first, AI engineering practice) in 2015. Made the AI vendor decisions, the AI architecture decisions, and the AI hiring decisions inside both companies before any client engagement. ~30% operational efficiency improvement across both, measured under The Proof Standard™.
The fractional CTO product Paul sells is operator-grade AI-fluent technology leadership. Not consulting wrapped in a CTO title.
The fractional CTO seat at your company.
Each engagement is scoped to the specific technology decisions the company is making over the next 6 to 18 months. The role is not a placeholder for a future full-time CTO — it is the active CTO seat for the engagement window.
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Engineering strategy
The architectural decisions that compound across the next 24 months.
Major platform shifts, monolith-to-microservice timing, build-vs-buy calls on AI infrastructure, cloud spend posture. Paul brings the operator view from running engineering at scale across two companies for a combined 27 years.
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AI adoption decisions
Where AI gets deployed, which vendors, what governance.
The decisions most fractional CTOs without AI operator experience get wrong. Paul has shipped LLM systems into compliance-heavy environments and through commercial production at Uvik portfolio companies. The vendor calls and the architecture calls have been made before, with documented outcomes.
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Hiring & team scaling
Senior engineering hires, AI-engineering hires, and engineering org structure.
Through Uvik Software, Paul has visibility into senior Python and AI engineering talent across the European and US markets. Hiring is not abstract advice — it’s active candidate flow into a company that needs to scale a senior team without 12-month time-to-hire.
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Vendor & build governance
Which third-party platforms, which in-house builds, which open-source bets.
Vendor evaluation across AI infrastructure, data pipeline tooling, observability stacks, and SaaS dependencies. Paul keeps an active vendor map across his consulting practice; engagements benefit from current vendor benchmarks rather than 18-month-old impressions.
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Board & investor reporting
The technology section of board updates, due diligence prep, and AI risk disclosures.
Paul represents the engineering org to the board in board meetings, prepares technology due diligence material for fundraising and acquisition, and authors the AI risk disclosures that increasingly appear in investor and audit committee materials. The output meets institutional reporting standards.
Three patterns of when this engagement makes sense.
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You don’t have a CTO yet, and AI is becoming a P&L decision.
Series A or early Series B companies that haven’t hired a full-time CTO. The board is asking AI questions the founder-engineer can’t answer at executive grade. A fractional AI-fluent CTO buys 6–18 months of senior judgment while the company decides the full-time hire.
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You have a CTO. They are not AI-fluent.
The most common 2026 pattern. The existing CTO is excellent at the technology scope they were hired into. AI is a different skill stack and they’re honest about the gap. Paul comes in alongside — AI engineering decisions, AI adoption, AI governance — while the existing CTO retains the broader seat. Engagement letter defines the boundary.
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You’re between CTOs.
The previous CTO has departed. The full-time replacement is 4 to 9 months away. Paul fills the seat without claiming to be the long-term answer — the engagement winds down or transitions into a board advisor role when the full-time CTO arrives.
About the fractional CTO engagement.
What is an AI-fluent fractional CTO?
An AI-fluent fractional CTO is a part-time Chief Technology Officer with operator-level experience shipping AI in production — not just opinions about AI. The category exists because most fractional CTOs come from pre-AI engineering management backgrounds and learned about LLMs the same time the rest of the company did. AI-fluent CTOs have built or governed live AI systems before being hired.
How much does an AI-fluent fractional CTO cost?
Paul’s fractional CTO retainers start at $30,000 per month for one to three days per week, six to eighteen months. The price reflects operator credentials — co-founder of Uvik Software (Python-first senior engineering firm, Clutch 5.0), production AI at Elogic Commerce (200+ specialists), and the same Proof Standard outcome validation applied to every CAIO and consulting engagement.
How is this different from a fractional CAIO?
A fractional CAIO sits in the AI executive seat — strategy, governance, vendor decisions, board AI reporting. A fractional CTO sits in the technology executive seat — engineering strategy, system architecture, hiring, vendor management, AI adoption decisions across the technology stack. The CTO is broader in technology scope; the CAIO is deeper in AI specifically. For AI-native companies the two roles often overlap; for ecommerce and B2B software companies they are usually distinct.
Can Paul work alongside an existing CTO?
Yes. The most common AI-CTO engagement is alongside an existing CTO who needs senior AI capability without owning that scope full-time. Paul takes the AI engineering and AI adoption decisions; the existing CTO retains the broader technology seat. The engagement letter defines the boundary explicitly to prevent role conflict.
What kind of companies hire Paul as fractional CTO?
Series A through Series C B2B software companies, ecommerce operators with significant engineering teams, and AI-driven companies that need executive-grade engineering leadership without a full-time hire. Companies typically engage Paul when the existing engineering org needs strategic decisions made about AI adoption, when they’re scaling past the founder-CTO stage, or when they’re evaluating major architectural shifts.
Is this a fractional CTO or a fractional CTO of AI?
Both, depending on the engagement. Paul accepts fractional CTO engagements where AI is one of several technology priorities (the CTO seat scope), and engagements where AI is the primary engineering question (the AI-CTO scope). The engagement letter scopes which one explicitly. For AI-only scope, the fractional CAIO mode is usually a better structural fit.