Lead Engineers matter more in the age of AI.

AI is making code cheaper. It is not making good technical judgement cheaper.

That is why I think Lead Engineers matter more now, not less. I am hiring one.

The easy version of the AI story is that a coding tool makes everyone faster. Sometimes it does. But faster code generation is not the same as faster progress on a system that has to survive its next ten changes.

Someone still needs to ask the questions that do not fit in a prompt:

1. What are we actually modelling?
2. Who owns this capability when several teams depend on it?
3. What happens when the contract changes, the old path cannot disappear, or the system reaches a new scale?
4. Which shortcut gets us through this quarter and makes the next four worse?
5. How do we help the team make those calls without creating a queue in front of one experienced engineer?

That is Lead Engineering.

The job is not to say no

A good Lead Engineer is not the person who blocks work most confidently. They are the person who can turn a hard technical constraint into a route forward.

“We should not ship this as a permanent shim” is useful only when it comes with the next move:

1. Here is the smallest durable slice.
2. Here is what we can safely defer.
3. Here is the dependency sequence.
4. Here is the decision we need.
5. Here is what the fast path costs later.

That is how you protect a platform without becoming the team that stops everyone else shipping.

AI-first does not mean tool-first

I want every engineer to own an intentional local harness.

Not the same harness. That would be weird, and probably brittle. But every engineer should know which agents they use, what those agents are for, which tools and skills they can call, and where human judgement still matters.

The direction I want is simple:

1. AI writes more of the initial code.
2. Humans review it well.
3. When a review pattern is reliable, the agent takes it on without a human in the loop.

Human accountability does not mean a human needs to click through every predictable check forever. It means humans set the standard, understand the system, watch the outcomes, and step in when judgement is required.

The interesting work is building the practice around that change: useful agent roles, good tool boundaries, checks that catch the right failures, and a team willing to share what worked as readily as what exploded.

The multiplier test

The best Lead Engineers leave people stronger than they found them.

They do not take every difficult design and turn it into a private side quest. They coach a senior engineer through the design. They ask for a recommendation. They make the trade-off visible. They give someone room to run, then help when the edge gets sharp.

That is not softer leadership. It is how a team gets more capable without creating a permanent queue in front of its most experienced engineer.

I am hiring

I am looking for a Lead Engineer who likes that kind of work:

1. Deep systems and platform thinking.
2. Shared capabilities, APIs, data models, lifecycle problems, and long-term technical choices.
3. AI as an engineering practice, not a slide deck.
4. Making other engineers more capable.
5. Enough hands-on curiosity to keep changing how they build.

You do not need a public blog or a drawer full of side projects. But you probably tinker. You have probably changed your own workflow because the old one annoyed you. You care about the difference between a demo and a thing a team can rely on.

If that sounds like you, get in touch on LinkedIn.