AI Engineer

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

Job summary

Mane Consulting in Melbourne is seeking an AI Engineer to drive internal data analytics projects and deliver measurable impact across the company.

You will design, develop, and maintain AI systems using modern AI patterns, LLMs, RAG, agents, and AI-enabled decisioning while upholding quality, safety, and operational excellence.

This hands-on role offers opportunities to work with secure, scalable, and responsible AI in a pioneering industry leader.

Qualifications

• 3+ years of experience delivering production AI/ML systems.
• Strong foundation in AI, ML, statistics and analytics.
• Experience building scalable, production‑ready AI apps.
• Practical knowledge of LLMs, prompt engineering, RAG and agents.
• Ability to design AI architectures and integrate with enterprise data platforms.
• Understanding of MLOps/LLMOps, CI/CD, deployment and monitoring.
• Experience with testing, evaluation and reproducible delivery.
• Familiarity with data science environments supporting scalable delivery.

Responsibilities

• Design, develop and implement AI/ML solutions aligned to business needs.
• Build and integrate generative AI and LLM-based applications, including prompts and RAG pipelines.
• Develop custom AI agents with control flow, state management, retries and escalation paths.
• Build inference, orchestration and integration components using modern APIs and cloud services.
• Implement production-grade AI systems with VCS, testing, CI/CD and documentation.
• Design model evaluation and testing approaches for accuracy and reliability.
• Implement controls for AI security, privacy and responsible AI.
• Contribute to AI assurance, risk assessment and governance with technical evidence.
• Collaborate with teams to ensure alignment with enterprise data platforms.

Skills

AI/ML engineering

Production systems

AI fundamentals

LLMs & Generative AI

AI solution architecture

MLOps/LLMOps

CI/CD & deployment

Data platforms

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.