Market overview & salary guide

Three pockets of growth in software engineering

• High-context AI consumers. Engineers who command a team of agents to deliver at a scale a single IC previously could not. This comes with deeper commercial and product knowledge.

• AI engineers. Deep working knowledge of RAG, fine-tuning, evals, and agent engineering itself. Building the systems, agents, and products around the models.

• Staff engineers have seen disproportionate salary growth. Those who can take their technical seniority and context, apply AI tools, and the market is paying for it.

The experience curve

• Juniors who are AI-native are in demand again. They default to agentic tools, ship quickly, and have no old habits to unlearn. In the past 6 months we see a clear uptick in junior demand. If you are prepared to filter and screen hard, you can pick up some brilliant value talent who can add significant productivity to your team.

• Mids and seniors are stuck in the middle. Strong fundamentals, but the market is pickier on AI adoption. Candidates from bigger companies are often slower to have shifted their workflow.

• Staff and above sit above this dynamic. Their context and judgement compound with AI rather than compete with it. This is where we have seen the most salary growth.

Small teams, outsized impact

A small team with the right context and tools can now compete with much larger ones. Hiring strategy is shifting toward fewer, sharper people.

Talent availability

• Application volume and noise is high.

• The market is not rewarding "potential" or "transferable skills".

• Hiring is slower than it has been in years. Pace of change and slower economic growth are both factors.

Remote working

• Small teams often embrace remote and hybrid. Bigger companies, more office time.

• Fully remote remains a competitive lever, especially for Sydney-HQ’d companies in Australia’s toughest talent market. Pockets of talent across SE Queensland and cities like Adelaide actively market their skills into Sydney and Melbourne.

Convergence of product, engineering and design

The lines between functions are blurring. At larger companies, PMs are shipping. At smaller ones, engineers are doing the product work. Designers are moving further into the code.

Engineers should move closer to the customer, and the strategic and product vision of a company. Building workflows and practices around this means cross-functional teams can ship, build, and collaborate faster.

Build AI as a culture

Index for hires on the forefront. Those who have natural passion and curiosity with the energy to embrace change. Not because they know how today’s tools work better, but because they will know about tomorrow’s tools first. Most companies aren’t ambitious enough with AI. The models are far more capable than how they’re being used, which makes humans the bottleneck to AI output.

The pace of change is unlike anything we have seen. The ability to lean into it will be the single biggest factor in whether you stay ahead. The way to do this is hire the people who will help this become part of your DNA.

It is tough to generalise, but AI has disrupted talent pools significantly. Engineers who embraced high standards before can also be purists and resistant to this change. If you think of AI as leverage, getting the right team has never been more important.

Beyond AI

We are seeing the early stages of growth in physical tech, robotics and mechanical engineering.

If AI makes software cheap to build, the software layer inside a robot becomes the easy part. Companies compete on the physical problem instead.

Investors are looking for a refuge away from AI, and we are confident this becomes an area of growth over the next 6 to 12 months. If you are a software engineer with a chance to move into embedded systems, this is one of the most interesting and promising places to be.