The AI Systems Engineer you need

The person you need to build business AI is an AI Systems Engineer: someone who thinks in systems, communicates well, learns quickly and is excited about what AI makes possible.

You do not need a specialist in NLP, machine learning or model training simply because the work involves AI. Those backgrounds can be valuable, but they are not the defining qualifications for building systems with today's models. We look for people who can understand the business problem, work with experts and turn the available technology into something useful and reliable.

Systems thinking and communication

A systems thinker looks beyond the model or prompt. They understand how information, business judgment, tools, people and software work together. When a result is wrong, they can investigate whether the cause is missing information, an unclear decision, the workflow or the implementation.

Communication is part of that engineering. The engineer needs to ask useful questions, make their reasoning understandable and work directly with the people who know the business. They help establish what the AI should do and turn expert feedback into improvements. That is central to Performance-Driven Development.

Look for people already building and using AI

The strongest signal is someone who is already spending hours each day building with AI and using it in their own work. They are trying new tools, testing ideas and finding different ways to get things done without waiting for an employer to tell them to start.

The hours themselves are not the qualification. They reveal curiosity, initiative and a desire to work differently. That matters more than a credential or familiarity with a particular framework. The technology will change; you want someone eager and able to change with it.

Ask what they are building now, how AI has changed their own work and what they tried that failed. Their answers should show how they learn and adapt, as well as what they can produce.

Hire for the new playbook

AI makes it possible for smaller teams to create more value. Hiring people to reproduce the old development process misses that opportunity. Look for engineers who want to reinvent how work gets done, including their own.

That is the kind of engineer we bring through our Forward Deployed Engineer model. Working alongside your people, they help build the solution and develop the team's ability to work in a new way. AI-native product teams explains how that extends to shared knowledge, communication and decisions.

Our new playbook explains the shift in engineering priorities. Our principles explain why learning speed, velocity and small expert teams matter as AI keeps advancing.