Rate pain, slower confidence
May 2026 was not a frozen tech hiring market, it was a selective one. The RBA’s cash rate sitting at 4.35%, after another warning about a “rough” time ahead for households and business, is still doing what higher rates always do, it makes leaders cautious, slower and far more allergic to risk. That showed up again in Sydney hiring, where teams were still approving critical roles, but the bar for sign-off was much higher than it was a year ago.
I’m seeing the same pattern across engineering, data, AI and security, fewer broad searches, more tightly defined mandates, and far more pressure to prove why a role exists now. SEEK’s hiring and salary data continues to show tech jobs still advertised, but the market is more uneven than it looks on the surface, with the strongest demand concentrated in roles tied to revenue, risk reduction or AI delivery. Anything that smells like “nice to have” gets pushed back. Anything that looks like operational leverage gets approved.
LinkedIn Talent Insights tells the same story in a different language, more candidate movement in niche capability areas, but longer decision cycles and more competition for proven specialists. The days of posting a generic “full stack engineer” brief and expecting a clean shortlist are mostly gone. Employers want evidence, not ambition.
AI keeps moving the goalposts
AI hiring is still the biggest structural shift in the market, and May made it obvious that AI-related work is no longer a side project. It is now embedded in product roadmaps, platform work and customer experience, which means the hiring brief is changing faster than most teams can write it. I’m seeing far more demand for people who can actually build, deploy and measure AI systems, not just talk about them.
McKinsey’s latest AI research keeps reinforcing what employers already know, companies are moving from experimentation to implementation, and the value is increasingly tied to operational use cases rather than isolated pilots. In Sydney, that translates into demand for applied machine learning engineers, AI product managers, data engineers who understand model pipelines, and platform people who can ship securely. The market has stopped rewarding vague “AI enthusiasm”. It wants proof of production impact.
Stack Overflow’s Developer Survey is useful here because it shows how quickly the developer stack is being reshaped by AI tooling. Developers are using AI assistants more, but the frustration is clear, they still need strong fundamentals, debugging skill, and real systems thinking. That is exactly why employers are now screening harder for people who can separate signal from hype. If a candidate cannot explain what they shipped, what improved, and how they measured it, they are getting filtered out.
In practice, that means the strongest AI hiring is happening in three buckets, internal productivity, customer-facing product features, and data/automation infrastructure. The weakest briefs are the ones asking for “someone who knows AI” without a business problem attached. Those roles linger. The specialised ones move fast.
Engineering and data are splitting
Engineering demand has not disappeared, but it has split into two very different markets. On one side, there is steady appetite for experienced platform, backend and cloud engineers who can reduce complexity, improve throughput and support AI-enabled systems. On the other, there is a much flatter market for generalists, especially where the work is feature delivery without any clear strategic edge.
That split matters because employers are now buying precision. They want distributed systems experience, cloud-native architecture, observability, cost discipline and stronger product sense. If a team is hiring engineers in May 2026, they are usually not doing it to “build capacity”, they are doing it to fix something specific, either performance, AI integration, technical debt or release velocity.
Data is following a similar path, but with more pressure attached. The strongest demand is for data engineers, analytics engineers and senior data scientists who can work close to the business and ship outcomes, not just models or dashboards. The weaker end of the market is still full of people whose work stops at reporting, and that is where the gap is widening.
There is also a much tougher standard for data science. Employers are asking for practical experimentation, causal thinking, LLM evaluation, prompt optimisation, feature engineering and measurable uplift. A lot of candidates still present as if it is 2022, when “we built a model” was enough. It isn’t anymore. The question now is, did it change the decision, save money, lift conversion, reduce churn, or improve speed?
SEEK’s category data keeps showing that the broader technology market remains active, but I would not call it generous. It is active in pockets. The best data and engineering candidates are still being moved quickly, but only when the job is sharp and the employer is decisive. The mediocre briefs are getting no attention.
Security and DevOps stay sticky
If there is one area that remains stubbornly resilient, it is cybersecurity. The reason is simple, risk does not get optional just because budgets are tight. Boards still want better control, regulators are still tightening expectations, and the cost of getting security wrong is too obvious to ignore. That keeps demand steady for security engineers, GRC specialists, cloud security people, and incident response capability.
I’m seeing continued appetite for candidates who can work across engineering and security, especially people who understand identity, cloud posture, application security and secure-by-design delivery. Pure policy experience is not enough in many Sydney teams now. Employers want operators who can influence engineers and move controls into the build process.
DevOps is sticking for the same reason. Teams are still under pressure to release faster, reduce cloud waste, harden environments and support more AI-heavy workloads without blowing up reliability. So the hiring focus is shifting toward platform engineers, SREs, cloud infrastructure specialists and DevOps people who can actually improve delivery economics, not just maintain pipelines.
This is where the market gets pragmatic. A company might freeze one product team, then hire a security lead and a platform engineer in the same week because the business case is clearer. That is not contradiction, it is prioritisation. The cost of delay in infrastructure and security is easier to justify than the cost of missing a generic headcount target.
What I’m seeing on the ground in Sydney
At the coalface, May felt like a month where employers became more disciplined and candidates became more selective. Strong candidates were still moving, but only where the role had real substance, strong leadership and a credible problem to solve. People are much less willing to jump for a vague title or a marginal pay bump if the business case is weak.
There is also more scrutiny on senior hires. Teams want leaders who can operate in ambiguity, but they also want evidence of delivery, especially around AI adoption, cost control and cross-functional influence. A polished story is not enough. They want the numbers, the trade-offs and the lessons learned.
From a salary and negotiation point of view, the market is not overheating, but specialist talent still commands a premium. The premium is just narrower and more defensible than it was in the boom cycle. The people who can credibly combine AI fluency with deep engineering, data or security expertise are the ones with leverage.
The other change I’m seeing is the rise of “must-have” capability in every brief. Teams are cutting headcount, but they are not lowering expectations. In many cases they are raising them. That is why hiring feels slower, because the shortlist is smaller and the decision-making is more cautious.
A selective market, not a dead one
May 2026 looked like a market where budget caution was still real, but AI-related hiring was no longer optional. Employers who are still treating AI as an innovation layer rather than an operating requirement are already behind. The smarter teams are hiring for specific outcomes, better automation, better product features, better risk management, better data capability.
That is why I keep coming back to the same point, this is not a frozen market, it is a selective one. The employers who move quickly on clearly scoped AI, data, engineering and security roles will keep winning the better talent. The rest will keep rewriting briefs, debating titles and wondering why the shortlist never lands.
My read is simple, the hiring market in Sydney is still open, but it is unforgiving. Generalists are under pressure, specialists are in demand, and proof of impact matters more than ever. That is the shape of the market right now, and I do not see that changing quickly while rates stay high and AI keeps resetting the benchmark for what good looks like.
The future is bright, let’s go there together!
Thanks for reading,
Cheers Keiran
Big Wave Digital.
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At Big Wave Digital, Sydney’s leading digital, blockchain and technical recruitment agency, we have deep connections, experience and proven expertise, and the ability to achieve a win for all parties in the challenging recruiting process. We can connect to highly coveted digital and tech talent with the world’s best employers.
Keiran Hathorn is the CEO & Founder of Big Wave Digital. A Sydney based niche Digital, Blockchain & Technology recruitment company. Keiran leads a high performance, experienced recruitment team, assisting companies of all sizes secure the best talent.
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