Recruiting an AI-First CTO for a Polish SaaS platform for marketing automation (NDA)

Executive Summary

As part of a confidential Executive Search process (NDA), we recruited an AI-First Chief Technology Officer for a Polish technology company operating in the SaaS/martech sector—a platform for automating advertising campaigns and marketing activities, serving local businesses and social media agencies. Due to the strategic nature of the role and plans for a major transformation of the IT department, the project was conducted in strict confidence—without disclosing the client’s name, without publishing job postings, and without any external communication.

The first suitable candidates were presented to the client just 11 days after the project began, and we completed the entire process—from start to the hiring of the final candidate—in 5 weeks. A total of 192 candidates went through the Direct Search funnel, of whom the 4 best-matched profiles made it to the shortlist. The client chose one of these individuals—an experienced technology leader with a proven track record of AI-first transformations in mature product organizations.

The key challenge of the project was to find a CTO who combines three competencies that rarely go hand in hand: real, documented experience in implementing AI tools in manufacturing processes (rather than just a superficial familiarity with buzzwords), the ability to strategically redesign the entire IT department’s operations to become AI-native, and the ability to lead a team through a profound cultural and operational transformation. Most CTOs on the Polish market today claim to have knowledge of AI, but only a small group has a track record of concrete implementations that have measurably increased the productivity of the engineering team—and it was precisely this group that was our true target.

The newly hired CTO brings to the organization years of experience in scaling engineering teams in a product environment, as well as hands-on experience implementing coding agents, LLMs in code review and QA automation—which directly supports the client’s strategic goal: transforming the entire IT department into an AI-native organization capable of delivering new product features faster and competing more effectively in international markets.

The recruitment challenge

Recruiting a CTO for an AI-first, mature SaaS product is one of the most challenging executive search assignments on the Polish market—it involves a limited pool of candidates, the need to verify actual competencies (rather than mere claims), and complete confidentiality throughout the process.

1. A genuine “AI-first” approach, not just a buzzword

The biggest technical challenge was distinguishing between candidates who had actually implemented AI in manufacturing processes and those who merely claimed to have knowledge of the subject. By 2025/2026, virtually every CTO will list “AI,” “LLM,” and “GenAI” on their resume—but only a small group will have completed specific projects that have measurably changed the way the engineering team works.

The client needed someone with proven experience in implementing, among other things:

• coding agents (Claude Code, Cursor, GitHub Copilot Workspace) in the day-to-day work of a development team
• The Role of LLMs in Code Review and Code Quality Assurance
• QA and test automation using AI
• AI in DevOps processes and engineering support
• productivity metrics that demonstrate the actual impact of these implementations on the team’s work pace

2. A hybrid profile: strategist, practitioner, and transformation leader

The CTO was not meant to be a traditional “technical director” who merely oversees product delivery. The role combined three areas of responsibility:

• defining a technology vision and an AI-first strategy for the entire IT department
• practical knowledge of tools and the ability to personally lead implementations, rather than just delegating
• Guiding the team through a cultural shift —convincing engineers that AI is a support rather than a threat, and establishing new work standards

Such a hybrid profile is particularly hard to find, as most experienced CTOs specialize in one of these areas—rarely combining strategic vision with a practical, hands-on approach to new tools.

3. Full confidentiality of the project (NDA)

The project was carried out in stealth mode—without disclosing the client’s name, without publishing job postings, and without any external communication. This meant that the entire process had to rely solely on Direct Search, and initial conversations with candidates had to be conducted without the ability to use the client’s brand as a selling point.

This made it difficult both to attract candidates (since the company name didn’t have the chance to “make an impression”) and to assess their suitability—candidates had to agree to in-depth interviews before they knew exactly who they were talking to.

4. Aligning with the culture of a mature product scale-up

The client is neither an early-stage startup nor a large corporation, but a mature product company with an established work culture. The CTO had to fit into an environment where the management team is heavily involved in operations, the team is accustomed to a specific way of working, and the product is already up and running and generating revenue—which meant that the AI-first transformation had to take place without disrupting current operations.

Our Approach

Due to the confidential nature of the project, the limited pool of viable “AI-first” candidates, and the hybrid nature of the role, the process was designed as a targeted executive search conducted in stealth mode —relying exclusively on direct search and early verification of hard criteria.

1. Clarifying the actual profile of an AI-First CTO

We began the process with a workshop involving the client’s management team, during which we distinguished between hard, non-negotiable criteria and those that could be treated flexibly. We considered the following to be hard criteria: documented AI implementations in the manufacturing process, experience managing an engineering team of several dozen people, and a practical, “hands-on” approach to new tools. We considered a specific technology stack or experience in the martech industry to be “nice-to-haves.”

2. Targeted Direct Search under an NDA

The process did not rely on publishing job postings —this was not possible under the NDA. We conducted a market survey of Polish CTOs, VPEs, and Heads of Engineering at companies that met one of the following criteria:

• Established Polish SaaS companies and product scale-ups with teams of several dozen people
• technology companies that have publicly announced the implementation of AI in their manufacturing processes
• international product companies with engineering divisions in Poland where an AI-first transformation is already underway

We initially approached candidates in a "stealth" manner—without revealing the client’s name, but providing a detailed enough description of the role to filter out those who weren’t genuinely interested in AI transformation.

3. Putting “AI-first” to the test through concrete actions, not just declarations

A key methodological decision in this project was to assess participants’ actual experience with AI during the initial interview —by asking for specifics rather than general statements. Instead of asking, “Have you worked with AI?”, we asked:

• What specific tools did the candidate implement in their team, and at what stage of the process?
• What the implementation process was like —team resistance, initial experiments, scaling
• Which productivity metrics changed after implementation, and by how much?
• what didn't work and what the candidate learned from those failed experiments

This approach allowed us to quickly distinguish between candidates who merely made claims and those with a proven track record—and focus exclusively on the latter group.

4. Competency- and culture-based selection

Each candidate who passed the initial AI screening was evaluated in a 45-minute video interview conducted by a Fast Forward Solutions consultant. During the interviews, we assessed their experience managing a large engineering team, their leadership style in the context of cultural change, their motivation to work at a mature product scale-up, and their willingness to work in strict confidentiality—before learning the client’s name.

5. Confidential cooperation with management

The client’s decision-making process was streamlined as much as possible and conducted in direct contact with the CEO and key members of the executive board. It included a review of Fast Forward Solutions’ recommendations, an online meeting with the executive board (still in stealth mode for some candidates), and then an in-depth meeting after the client’s name was disclosed. Thanks to efficient communication and quick decisions on both sides, the first profiles were sent to the client as early as the 11th day of the project, and we completed the entire process in 5 weeks.

The selected candidate

An experienced CTO with a proven track record in AI-first transformation

The candidate we ultimately hired is an experienced technology leader with many years of experience scaling engineering teams in mature product organizations. Due to the confidential nature of the project, we are unable to disclose details about their career path or previous employers.

Key competencies

The candidate has proven experience in implementing AI tools in manufacturing processes—such as coding agents, large language models (LLMs) for code review, and QA automation—with measurable results in the form of increased team productivity. They combine this with years of experience managing a large engineering department and guiding teams through cultural and operational changes.

Why this candidate?

The decision was based on a combination of genuine, rather than merely claimed, AI-first experience and a mature leadership style suited to a product-driven scale-up. In a project where the primary criterion for eliminating candidates was verification of actual AI implementations, this profile stood out with concrete examples and metrics—while also demonstrating an understanding that the IT department’s transformation must take place without disrupting the ongoing product delivery.

The process and key figures

The recruitment process for the AI-First CTO was designed as a targeted executive search conducted in stealth mode—focused on the quality of the shortlist and the speed of execution, despite the constraints imposed by the NDA.

What does this mean in practice?

Narrowing the shortlist down to four carefully selected candidates—from a pool of 79 profiles—allowed the client to focus exclusively on individuals with a proven, documented track record in AI-first transformation, without having to review dozens of CVs full of claims.

The speed of the process was made possible by three key methodological decisions: targeted Direct Search conducted in stealth mode, verification of the AI’s recommendations through concrete examples during the very first interview with the candidate, and direct collaboration with the client’s management team to ensure a rapid decision-making process. As a result, the first matched profiles were presented to the client as early as the 11th day of the project, and the final candidate was hired in the 5th week —a result significantly better than the market standard for confidential CTO recruitment.

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