Specialisation — GenAI

AI Engineers (GenAI / Agents)

AI Engineers building GenAI and agentic systems on top of foundation models. The strongest candidates are not just prompt engineers.

The Role

What GenAI Engineers Do

These engineers build software products on top of foundation models — RAG systems, tool-calling workflows, agents, LLM-powered applications, evaluation frameworks and production guardrails. The strongest candidates understand product engineering, APIs, latency, data flow, orchestration, evaluation and safe execution in production.

Roles We Place
AI Engineer
GenAI Engineer
LLM Engineer
AI Application Developer
Conversational AI Engineer
AI Solutions Engineer
Technical Skills

Technologies We Screen For

We technically vet every GenAI candidate against these core skills.

LLMs RAG Vector Databases Prompt Engineering LangChain LlamaIndex OpenAI API Anthropic API Fine-tuning RLHF Embeddings Agent Frameworks Function Calling Guardrails Python TypeScript FastAPI
Market Insight

What the Market Looks Like

GenAI engineering is the hottest role in tech right now. Every company wants to build with LLMs, but few engineers have production experience. The field moves so fast that 6 months of hands-on experience often matters more than years of traditional ML. We specialise in finding engineers who've actually shipped GenAI products, not just built demos.

FAQ

Common Questions About Hiring AI Engineers (GenAI / Agents)

What's the difference between an AI Engineer and an ML Engineer in the GenAI space?
AI Engineers in the GenAI space focus on building applications on top of foundation models (LLMs) — RAG systems, agents, chatbots, and AI-powered features. ML Engineers typically train models from scratch. GenAI engineers are more application-focused, while ML engineers are more model-focused. Both are valuable, and the best teams have both.
How do you vet GenAI engineers given how new the field is?
We look for hands-on production experience: have they built RAG systems that handle real user queries at scale? Do they understand prompt engineering beyond basics? Can they evaluate and compare different LLM providers? Have they implemented guardrails and safety measures? We also assess their ability to learn rapidly, since the tools change monthly.
Should we hire a GenAI specialist or upskill existing engineers?
It depends on your timeline and ambition. For greenfield GenAI products, hiring a specialist who's already shipped similar systems saves months of learning. For adding AI features to existing products, upskilling a strong software engineer with GenAI training can work well. We can advise on the right approach during our briefing call.
What salary range should I expect for GenAI engineers?
GenAI engineers in Australia currently command $170K–$280K+ for permanent roles, with senior/lead positions at the higher end. Contract rates are $900–$1,500/day. The market is extremely competitive — top candidates often have multiple offers. Speed in your hiring process is critical.

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