AI Engineer

Mane; Melbourne; On-site; AUD 120,000 - 170,000; Full time

Job summary

Mane Consulting in Melbourne seeks an experienced AI Engineer to lead internal data analytics projects and deliver measurable impact across the business.

You will design, develop, deploy, and maintain AI systems, applying modern AI engineering practices, from prototyping to production, with a focus on security, reliability, and governance.

Join a pioneering team that embraces responsible AI, MLOps and scalable architectures to enable data-driven decisions.

Qualifications

• 3+ years of AI/ML engineering delivering production systems.
• Strong foundation in AI, ML, statistics and analytics.
• Experience building scalable, production-ready AI applications.
• Practical knowledge of LLMs, prompt engineering, RAG, and AI patterns.
• Ability to design AI architectures integrated with enterprise data platforms.
• Understanding of MLOps/LLMOps, CI/CD, deployment, monitoring.
• Experience with reproducible, scalable data science environments.

Responsibilities

• Design, develop and implement AI/ML solutions aligned to business needs.
• Build and integrate generative AI and LLM-based applications.
• Develop custom AI agents with control flow and state management.
• Build inference, orchestration and integration components with cloud services.
• Implement production-grade AI systems with CI/CD and documentation.
• Design model evaluation for accuracy, robustness, safety.
• Implement AI security, privacy and governance controls.
• Contribute to AI assurance and risk assessment activities.

Skills

AI/ML engineering

Production systems

LLMs and generative AI

Data analytics

Tools

CI/CD pipelines

Cloud services (AWS/Azure)

Job description

Get recognition and reward working with this a pioneering industry leader, as they embark on a transformative journey! The AI Engineer will drive internal data analytics projects serving all areas of the company.

You’ll design, develop, integrate, deploy, and maintain AI systems that deliver measurable impact. From experimentation and prototyping through to production implementation, monitoring, optimisation, and retirement, you’ll apply contemporary AI engineering practices to build secure, scalable, reliable and responsible AI solutions.

This is a hands?on engineering role for someone who wants to work with modern AI patterns, LLMs, RAG, agents, generative AI, intelligent automation, and AI?enabled decisioning, while contributing to a mature engineering culture grounded in quality, safety, and operational excellence.

What You’ll Work On

• Design, develop and implement AI/ML solutions aligned to business needs and strategic objectives.
• Build and integrate generative AI and LLM?based applications, including prompt engineering, RAG pipelines, agents and AI?enabled workflows.
• Develop custom AI agents with robust control flow, tool definitions, state management, retries, escalation paths and stopping conditions.
• Build inference, orchestration and integration components using modern APIs, frameworks and cloud services.
• Implement production?grade AI systems using software engineering best practice – version control, testing, CI/CD, automated deployment and documentation.
• Design and execute model evaluation and testing approaches (accuracy, robustness, reliability, bias/fairness, hallucination, safety).
• Implement controls for AI security, privacy, data protection, access management and responsible AI.
• Contribute to AI assurance, risk assessment and governance activities with technical evidence and advice.

What You Bring

• 3+ years of experience in AI/ML engineering with a proven track record delivering production systems.
• Strong foundation in AI, machine learning, statistical modelling and analytical techniques.
• Experience developing scalable, production?ready AI applications using modern software engineering practices.
• Practical knowledge of LLMs, prompt engineering, RAG, embeddings, agents and generative AI patterns.
• Ability to design AI solution architectures and integrate AI capabilities with enterprise systems and data platforms.
• Understanding of MLOps/LLMOps, CI/CD, deployment, monitoring and lifecycle management.
• Experience designing and implementing testing and evaluation approaches.
• Familiarity with data science platforms and analytical environments supporting reproducible, scalable delivery.

Mane Consulting specialise in Data & Analytics.