Senior AI Engineer

Mane Consulting; Melbourne; On-site; AUD 120,000 - 160,000; Full time

Job summary

Mane Consulting is seeking an AI Engineer to lead design, development and deployment of AI/ML solutions across the business. You will work with modern AI patterns, LLMs, RAG, agents, and AI-enabled workflows in a mature engineering culture focused on quality, safety, and operational excellence.

The role involves building scalable, production-ready AI applications, integrating AI capabilities with enterprise systems, and applying governance, testing, and monitoring practices to ensure responsible

Qualifications

• 3+ years of experience in AI/ML engineering delivering production systems.
• Strong foundation in AI, machine learning, statistics.
• Experience building scalable production AI apps with modern engineering practices.
• Knowledge of LLMs, prompt engineering, RAG, embeddings, agents, generative AI patterns.
• Ability to integrate AI capabilities with enterprise data platforms.
• Understanding of MLOps/LLMOps, CI/CD, deployment, monitoring and lifecycle management.

Responsibilities

• Design, develop and implement AI/ML solutions aligned to business needs and objectives.
• Build generative AI and LLM-based applications, including prompt engineering and RAG pipelines.
• Develop custom AI agents with robust control flow, 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 practices — version control, testing, CI/CD, 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.

Skills

AI/ML engineering

LLMs

RAG

CI/CD

Tools

CI/CD pipelines

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.