The board has asked for the AI plan, the budget line says “data and AI capability”, and you have to turn it into a hiring plan with names on it. The data team you have is three people and a warehouse migration. Every CV that arrives says AI, and the people who sound best in the interview are the ones who have presented the most pilots. You need to know who to hire first, what they should already have done, and whether the package will reach them.
That is the brief we hear most often in data and AI, and it is a hiring question before it is a technology one.
Altura is a data and AI recruitment agency headquartered in Sydney and working nationally, recruiting heads of data, chief data officers, data platform leads, ML engineering leads, data product owners, analytics engineers and AI governance leads, permanent and contract.
Our strength here is the network. We know these people and we talk to them every week: the platform leads who made the foundations work, the ML engineers who have kept a model running in production, the data product people sitting in the business. We would rather say that plainly than overstate it. The data and AI work rests on close to 20 years in technology and transformation search, and on the fact that most of the people we introduce were not looking when we rang.
What we recruit
Permanent and contract, for enterprise, mid-market, private equity-backed and high-growth businesses:
- Chief data officers and heads of data
- Data platform leads
- ML engineering leads
- Data product owners
- Analytics engineers
- AI governance and model risk leads
Across financial services, superannuation, wealth, capital markets, professional services, technology and the public sector.
What we assess for
Every CV in this market says AI. We assess for production: a named model or data product that has been live for a year, a business outcome with a number against it, and a plain account of what broke and what they changed. In conversation we ask about the data decision they reversed, who signed off the baseline and what the number did once the pilot stopped being watched. People who have carried production talk in specifics. People who have presented it talk about potential. Referees come from the business side, not only the technical team.
We assess the brief as well. If it asks for a head of AI when it needs a platform lead, or the package will not reach the people who have shipped to production, you hear it in week one. For the hiring order that holds up, read AI past the pilot: who you actually need, and in what order.
Permanent, contract or retained
Contract and interim. For data engineers, analytics engineers and ML engineers building against a scoped product, and for interim data leadership, we draw on people we have worked with before. First assessed people within a day or two of the brief, with a view on how they worked last time.
Retained search. For the head of data, chief data officer, platform lead and ML engineering lead, the seats the business must own. Three to six weeks from brief to accepted offer: a comp verdict in week one, an assessed shortlist in weeks three to four, then offer management through to acceptance. The fee is staged in thirds, the search is exclusive and the appointment carries a twelve-week replacement guarantee.
Permanent, exclusive. For permanent roles below the leadership seats, the same assessment on an exclusive, success-fee basis.
We check in with you and the person at 30, 60 and 90 days after the start. In data and AI the third check-in matters most: it is usually when the first production decision has landed on the new person’s desk.
Why clients come back
Altura was founded and is led by Mark King after close to 20 years in technology and transformation search and more than 400 searches across his career. More than 90 per cent of Altura clients return. The person who takes the brief runs the search, tells you early if the brief or the package will not reach the market, and stays through the offer and the first 90 days.
More on how we think in data, AI and analytics, on the retained search process, and on how we work with employers.
Questions clients ask
Head of data, or more precisely a data and platform leader, almost always. A head of AI with no governed platform beneath them spends the first year asking the data team for things it was never funded to do. Get the pipelines, definitions, access and cost under one accountable leader, add an ML engineering lead who has shipped to production, and revisit the head of AI question in eighteen months when there is something to be head of.
We ask for one model or data product that has been in production for a year and the number it moved. Then what broke, what they changed and which data decision they reversed. The answers separate people who carried production from people who were near it, and a referee from the business side settles it. We would rather introduce three people who have done it than ten whose CVs say they have.
Yes. Data engineers, analytics engineers and ML engineers on contract, from people we have worked with before, with the first assessed people within a day or two of the brief. The condition we put on it is the one the article makes: contract capacity builds well when permanent leadership owns the platform and the handover is written into the contract. If you cannot name the permanent person who will own the model in eighteen months, we will say so.
Four pools, each with a shape. The banks and insurers that industrialised early, strong on governance and on running production under a regulator. The consulting AI practices, wide on breadth, so we ask who kept the model running after the engagement ended. The scale-ups, where people have shipped fast with small teams and rarely inside a risk function. And the academic route, strong on method, which produces excellent second hires once a platform lead is appointed. We know people in each, and most of them are not on a job board.
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