There isn’t a single “perfect” tech team anymore.

What we’re seeing across AI and engineering teams is a shift away from fixed structures and toward capability-led design. Teams are being built around what needs to be delivered, not what roles traditionally existed.

That shift has accelerated over the last 18–24 months.

Hiring volume is still below peak levels. UK software roles peaked at around 50,000–60,000 in 2022, dropped to roughly 20,000 in 2024, and have stabilised around 30,000–40,000 in 2026. The number of roles has reduced, but the expectation attached to each hire has increased.

At the same time, demand for senior and specialist engineers continues to rise. In markets like Germany, close to 40% of open software roles are mid-to-senior level, reinforcing a clear trend: fewer hires, more impact per hire.

For CTOs, this is not just a hiring trend. It’s a design constraint.

What high-performing teams look like now

The most effective teams we’re seeing in 2026 are smaller, more cross-functional and built around ownership.

They are not defined by strict frontend/backend splits. Instead, they are built around engineers who can take features or systems from idea through to production.

The core team typically includes:

Product Engineers (T-shaped)
Engineers who can operate across the stack and understand product context. They own delivery end-to-end and reduce the need for multiple handoffs.

Data Engineers
Now central to almost every modern product. Real-time systems, AI models and decision-making pipelines all depend on strong data foundations.

Platform / Infrastructure Engineers
Focused on enabling speed and reliability. As teams get smaller, internal platforms become critical to maintaining delivery pace.

AI / ML Engineers
Where relevant, these roles are increasingly product-facing. The focus is shifting from experimentation to running models in production.

What’s notable is not just the roles themselves, but how they operate together.

Ownership is clearer.
Dependencies are reduced.
Delivery moves faster.

What’s changing beneath the surface

AI is the biggest driver behind this shift.

Engineers are now able to work across multiple layers of the stack with the support of AI tools. Backend engineers can build frontend components. Product engineers can move from idea to deployed feature without relying on multiple specialist teams.

This is leading to a move toward T-shaped engineers — people with deep expertise in one area and broad capability across others.

It’s also changing what CTOs prioritise.

The focus is moving away from coverage of skills and toward leverage per engineer.

What CTOs are starting to build next

Looking ahead, the structure evolves further.

We’re starting to see early signs of what the next iteration of the tech team looks like.

AI-Native Engineers
Engineers who are not just using AI tools, but building systems that include AI as a core component. They think in terms of workflows, orchestration and behaviour over time.

Systems / Orchestration Engineers
As AI becomes more agentic, there is a growing need for engineers who can design how systems make decisions, call tools and operate autonomously.

Product + Engineering Hybrids
Engineers who understand user problems deeply and can translate them directly into shipped features without heavy product layering.

Fewer, More Senior Teams
The data already points in this direction. Higher seniority, fewer hires, greater ownership.

The real constraint: Alignment

The biggest challenge CTOs face isn’t access to tools or even talent.

It’s alignment.

When roles are unclear or ownership is fragmented, even the best engineers struggle to deliver impact. AI amplifies this. It increases what individuals can do, but also increases the cost of poor structure.

The teams moving fastest are the ones where:

• Roles are defined around outcomes

• Engineers understand the full system

• Ownership is clear from idea to production

What this means for hiring

Hiring strategies are evolving quickly.

The focus is no longer on filling roles. It’s on introducing capability.

That means:

• Hiring fewer, more experienced engineers

• Prioritising system thinking over narrow skill sets

• Looking for people who can operate across boundaries

• Aligning hiring closely with technical roadmap

The most effective hires are the ones who increase the capability of the entire system, not just their immediate function.

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The perfect tech team in 2026 isn’t defined by a fixed structure.

It’s defined by how well it can adapt.

AI is changing what engineers can do.
Markets are changing how companies hire.
And the best teams are evolving in response.

For CTOs, the question is no longer: “What roles do we need?”

It’s: “What capability do we need next, and who can deliver it?”