Job Description
We're looking for one thing: someone who builds. You use AI as a force multiplier — Claude or Copilot open on the second screen, prompting before Googling — and you ship real systems into production, not decks and prototypes.
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Most AI consulting stalls at the POC. We're hiring for the opposite problem: people who can take an idea from a client conversation to something running in an enterprise setting, with the governance, security and reusability that survives handover.
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You'll be the one making it. But you'll also be in the room when the problem is still fuzzy, so you need enough consulting instinct to run a discovery session, and enough architecture judgement to build something we don't have to rebuild.
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What You'll Do
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Build and productionise AI-enabled solutions — LLM apps, RAG, agents, automation — in real client environments
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Shape the problem — sit with clients early and translate technical options into business terms
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Make architecture calls that hold up — secure, explainable, supportable, reusable
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Drive efficiency — use AI tooling to compress delivery timelines, and know when not to use it
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Lift the team — raise AI fluency in the people around you
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What We're Looking For
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3-5+ years building software or data systems, with recent hands-on delivery
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Demonstrable AI tool fluency in your current role — you can talk specifics about what you've built and what you've abandoned
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Something you've taken to production, not just to demo
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Comfortable client-facing: you can run a workshop, not just attend one
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Experience in Agile delivery and comfort with rapid iteration
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AI-Specific Competencies (at least 3 of the following):
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LLM-based applications in production (RAG, prompt engineering, evals, fine-tuning)
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Hands‐on with AI coding assistants and AI‐driven DevOps pipelines at team scale
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Familiarity with AI/ML platforms (Azure OpenAI, AWS Bedrock, Vertex AI, or equivalent)
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Agentic AI frameworks (LangChain, AutoGen, CrewAI, or your own)
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Responsible AI: risk frameworks, bias mitigation, explainability, and the emerging Australian regulatory context
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Track record of measuring AI ROI and operationalising AI at enterprise scale
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Certifications in cloud AI platforms (Azure AI Engineer, AWS Machine Learning, Google Cloud AI)
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Background in data science, MLOps, or AI product management
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Published thought leadership or speaking experience on practical AI adoption
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Unlock job insights
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Your application will include the following questions:
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Which of the following statements best describes your right to work in Australia?
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What's your expected annual base salary?
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How much notice are you required to give your current employer?
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📌 Senior Ai Engineer (Victoria)
🏢 Blackbook.AI
📍 Victoria