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.
A fractional Chief Technology Officer is a senior engineering executive embedded part-time at the leadership table — typically one to three days per week over six to eighteen months — owning the technology decisions a company is too early or too lean to justify a full-time CTO for. The deliverable is executive judgment, not engineering hours.
The fractional CTO model emerged because the gap between “company has no senior engineering leader” and “company can justify a $400,000 fully-loaded CTO hire” is wider than most operating playbooks acknowledge. A scaling SaaS company at $5M-$30M revenue typically needs technology decisions made at the executive level — vendor commitments, build-vs-buy calls, hiring strategy, AI adoption sequencing — but the workload doesn’t justify a full-time hire and the cost can’t be absorbed.
The fractional CTO closes that gap. The seat is a real seat: weekly executive team participation, board-meeting presence, hiring authority within a defined budget, technology roadmap ownership. The structural difference from a traditional CTO is committed time (one to three days per week instead of five) and committed duration (a six to eighteen month engagement window instead of an open-ended employment relationship). Pricing reflects that — typically $15K-$50K per month versus $400K+ fully-loaded annual cost for a permanent CTO at this seniority.
The output is not delivery work. The fractional CTO does not write code, does not own delivery deadlines, does not manage individual engineers day-to-day. The output is the kind of decision a CEO would otherwise need to make alone, made instead with senior technology judgment in the room — backed by a track record of having shipped these decisions before.
Each scenario has alternatives. The fractional CTO is correct when the alternatives don’t fit the operating reality, not as a default.
Symptom: $5M-$30M revenue, technology decisions piling up at the founder level, no engineering executive at the table.
Alternative considered: hiring a permanent CTO directly.
Why fractional first: the company often doesn’t yet know what a great CTO hire looks like for its specific stack and stage. A six to twelve month fractional engagement clarifies the role definition before the permanent search starts. Saves a typical $200K cost-of-mishire on the wrong full-time CTO.
Symptom: existing CTO is excellent at infrastructure, scaling, hiring — but openly cautious about AI and the company is making AI-shaped commitments.
Alternative considered: replacing the CTO, or hiring an AI VP underneath them.
Why fractional second: Paul comes in alongside the existing CTO with explicit AI-decision authority. CTO retains operational ownership; fractional CTO owns AI adoption decisions. Lower-friction than a replacement, more decisive than an AI VP without executive authority.
Symptom: CTO has departed, search is running 6-9 months, technology decisions cannot wait.
Alternative considered: letting decisions slip until the new hire lands.
Why fractional bridges: AI vendor commitments, infrastructure decisions, and platform migrations have time-sensitive windows. Slipping decisions for six months has real cost. Fractional engagement covers the gap and produces a transition document for the incoming CTO.
The market range for a senior fractional CTO in 2026 is roughly $15,000 to $50,000 per month for one to three days per week of executive time. The wide range reflects the wide range of seniority and AI fluency on offer.
The lower end ($15K-$20K/month). Typically a senior engineering manager or director who has stepped out of a corporate role to consult. Strong on people management and operational leadership. Variable on AI fluency — most have managed AI projects but few have shipped AI in production at the executive level. Often serves earlier-stage companies (sub $10M revenue).
The middle ($20K-$35K/month). Former VPE or CTO from a successful exit, with a track record of one or two scale events. Good operational pattern recognition. AI fluency varies widely — some have led AI strategy, others are still learning. Common at $10M-$50M revenue companies.
The upper end ($35K-$50K/month). Multi-time CTO with operating company ownership currently. Has shipped AI in production with measurable P&L outcomes. Often combines fractional CTO work with board seats, advisory roles, or operating roles at portfolio companies. Serves $30M+ revenue companies and PE-backed integrations.
Paul’s pricing: $30,000/month for the standard one to three days per week engagement, with a six-month minimum. Position fits the upper end of the market based on operator credentials — currently CEO/Founder of Elogic Commerce (200+ specialists, founded 2009) and Uvik Software (Python-first senior engineering, founded 2015), with AI agents in production at both companies generating ~30% operational efficiency gains.
The economics favor the buyer significantly when the comparison is against a full-time hire. A permanent CTO at this seniority runs $300K-$450K base salary plus 0.5%-2% equity, before benefits and ramp time. The same executive judgment delivered fractionally lands at $360K annual without equity dilution and without a 90-day ramp. The economics flip if and only if the role fundamentally requires five-day-a-week presence — at which point the full-time hire is correct.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
The fractional CTO owns the company’s engineering executive seat broadly — engineering strategy, hiring, vendor governance, infrastructure decisions — with AI as one of several priorities. The fractional CAIO owns the company’s AI executive seat specifically — AI strategy, model and vendor decisions, AI governance, AI risk disclosure — and may sit alongside an existing CTO. Companies hire a fractional CTO when they need engineering leadership and AI is part of the mandate. They hire a fractional CAIO when AI is the primary leadership gap and engineering is otherwise covered. Read more on the fractional CAIO engagement.
The fractional CTO is correct when the workload genuinely doesn’t require five-day-a-week presence and the company is not yet certain what the permanent CTO role definition should look like. Common signals that a permanent hire is the right answer instead: more than three days per week of executive time required consistently, the role requires owning team morale and culture as a primary deliverable, the company has an active engineering organization of more than 30 people, or the company is post-Series B with a stabilizing leadership structure.
For some company stages and operating models, yes — particularly mid-market companies with stable engineering leadership underneath the executive layer, where the CTO seat is primarily about strategic decisions and stakeholder representation rather than day-to-day operational ownership. For early-stage companies that need a CTO who is also in the code and architecture reviews and managing on-call rotations, no — that role requires full-time presence. The honest test: list the activities the CTO seat needs to cover; if more than 60% require contiguous all-hands availability, hire full-time.
The CTO role splits roughly into four operating archetypes. The founder-CTO in early-stage companies sits closer to product and architecture than to people management. The infrastructure CTO in scaling companies owns platform reliability, security posture, and engineering organization design. The strategy CTO in mid-market and enterprise focuses on technology investment decisions, vendor governance, and board-level technology reporting. The innovation CTO in mature enterprises owns emerging technology bets, including AI. Paul’s engagements typically fit the strategy CTO or innovation CTO archetype with a strong AI emphasis.
Paul is based in Prague and takes fractional CTO engagements globally with active client geography across the United States (with a New York hub), the United Kingdom (London), continental Europe, and the Middle East. Most engagements run hybrid — one to two on-site days per quarter with the rest of the executive participation by video. See where Paul works globally.
Paul takes selective engagements globally with active client geography in four primary hubs. Each city page covers the local market context, sector mix, and engagement cadence specific to that geography.