AI/ML Executive Search in Australia

FleetGuru.ai, a B2B software scale-up on the Gold Coast, hired a Principal Agentic AI Lead through Digitalent, brought in to set the enterprise AI strategy and design the core agentic framework.

This was a location problem before it was a skills problem. Elite AI engineers are scarce on the Gold Coast in a way they are not in Sydney or Melbourne, and the brief needed a PhD-level architect willing to commit to a scale-up rather than a lab or a major. It also had to be someone senior enough to define the enterprise AI strategy and design the core agentic framework rather than execute somebody else’s, and to do that to the standard set by an AI product leader who reads twenty research papers a month. People who can do that are rarely looking, and rarely looking outside a capital city.

A marathon search rather than a fast one. The hire set the enterprise AI strategy, designed the core agentic framework and built the foundational data pipelines, then delivered a multilingual document extraction pipeline now heading for production. They are today the Lead AI Engineer and second in command on AI, and they are the reason the next hire could be briefed properly.

Five months later, FleetGuru.ai came back to Digitalent for the engineer who would build against that architecture, a Python-native AI engineer able to work across a C#/.NET codebase.

With the architecture set, the second search needed a builder, and the stack made that narrow. The core systems are C#/.NET with React and GraphQL, so a Python-native AI engineer had to be able to bridge that, work with the existing code and design APIs the engineering team could actually consume. The bar was set by a Chief AI Product Officer who reads twenty research papers a month and did not want data scientists. He wanted software builders who understood evaluation, latency, state machines and the Model Context Protocol.

Shortlisted in under a week. The six weeks to offer were mostly a month of pre-booked holiday, after which the candidate cleared a rigorous technical panel and was offered within a week, above the level the role had been briefed at. They own the time-series predictive maintenance modelling. Both hires work from outside the Gold Coast on hybrid arrangements agreed with the founders before the searches opened, which is what made either of them possible.