Over the past year at Gotfriends, we’ve identified a counterintuitive trend in the tech job market: senior research and development managers with impressive experience are finding it harder to move on to their next role. This is due to a deep shift in the role’s profile.
Based on our work with over 1,000 companies and in excess of 1,400 placements per year, it’s clear that requirements have changed faster than most managers have been able to adapt.
In R&D management roles, we repeatedly see candidates with strong leadership experience being rejected at advanced stages. This is not because they lack experience but because they don’t fit the new profile. Someone who was considered a highly sought-after R&D manager three years ago may now be seen as completely irrelevant if they lack experience with AI tools.
This shift is also reflected in salaries. An R&D manager with relevant AI experience now commands a monthly salary range of approximately NIS45,000 to NIS55,000, or higher, based on our updated 2026 salary benchmarks.
In contrast, managers without such experience are struggling not only to advance, but even to maintain their current salary levels. We’re seeing widening gaps between managers who fit the new profile and those who don’t. These gaps are reflected not just in opportunities, but also in compensation packages, reaching up to around 9 percent between candidates with AI experience and those without.
In the past, such managers were measured by their abilities in managing teams, meeting targets, and driving delivery. Today, that’s no longer enough. The introduction of AI tools has shifted the balance point.
Smaller teams produce more, processes that once required significant time and resources have become automated, and the ability to bring products to market quickly has become critical. In 2026, speed is no longer an advantage, it’s a baseline requirement.
But the change isn’t just about speed, it’s also about the nature of development itself. Increasingly, companies are moving toward development in which part of the business logic relies on models, not just traditional code. This requires R&D managers to understand how Large Language Models (LLMs) work, what their limitations are, and how to integrate them into existing systems in a stable and scalable way.
In parallel, the role has expanded significantly, with R&D managers are expected to understand the product, think at a business level, and be closely connected to Go-To-Market (GTM) strategy, meaning that they need to understand how development ties into product launches, customer needs, and actual revenue.
The ability to decide what not to build is just as important as the ability to build.
The companies we work with are no longer satisfied with familiarity with AI, they’re looking for real, hands-on experience. In practice, many candidates claim such experience, but only a minority have led AI systems in production, and that gap is now a key factor in hiring decisions.
Additionally, we’re seeing a shift from working with single models to more complex systems that include combinations of agents, connections to organizational data sources via Retrieval-Augmented Generation (RAG), and the use of Application Programming Interface (API) as part of the workflow. This means that an R&D manager is no longer just managing a team of developers but rather a system that integrates people, models, and automated processes.
Team structures are also evolving: fewer large teams of juniors, and more small, precise teams of seniors; less task management, more management of complex systems that combine people, models, and AI tools.
Today, R&D management is about managing a system, not just people. Those who don’t adapt to this shift are being left behind. This isn’t just another technological change, it’s a profound professional transformation. The market has already moved forward, the question is who is moving with it.
The writer is CEO of Gotfriends.