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Specialisms - AI Engineering - SaaS
Every SaaS roadmap now has an AI line item. Re:Sourced recruits the engineers who ship LLM features into live products, where the hard part is not the demo, it is evaluation, guardrails, latency and cost at real user volume.
The profile
The work is product-shaped: LLM features (copilots, summarisation, semantic search), retrieval-augmented generation over customer data, evaluation harnesses that catch regressions before users do, and the model-serving layer where latency and cost get decided. The build-versus-API call sits with these engineers too.
The differentiator is shipping AI into a product with real users, not a notebook. Engineers who have run evals, guardrails and cost controls in production are scarce and price at the top of the AI band. Typical stack: Python, vector stores, LLM APIs and orchestration, plus the product engineering to wire it into the app.
Where they come from
The strongest candidates come out of product-led SaaS scale-ups (Canva, Atlassian, SafetyCulture, Deputy, Linktree) and AI-native startups where AI is the product, not a feature. The useful profile blends product engineering with applied ML: people who can ship, measure and iterate, not only train.
Senior AI/ML engineers in Sydney price at AUD 180-220k base, 12-18% above senior software, base only, 25th-75th percentile of accepted offers. Frontier-lab calibre exceeds this. Full bands in the Salary Guide 2026.
Submit a brief
30 minute working session. No fee until placement. Replacement inside 90 days.