Maintenance & Training Manager (Aviation/Defense)

Cae; Sydney; On-site; AUD 120,000 - 180,000; Full time

Job summary

CAE in Sydney, Australia, seeks a Maintenance Training Manager Aviation Defense with hands-on AI/engineering leadership to design and deploy production AI applications and maintenance training systems.

You will co-own codebases, maintain Dockerized deployments, and lead CI/CD and observability efforts while collaborating with senior data scientists and stakeholders across Finance tools.

Qualifications

• Typically 3+ years of hands-on experience in AI Engineering, Software Engineering, or Data Engineering building production-ready data or AI applications.
• Core Technical Stack: Python, SQL; experience with RAG frameworks, vector databases, Docker, CI/CD, API integrations, and cloud platforms.
• Strong communication and collaboration skills with the ability to work with both technical and non-technical stakeholders.

Responsibilities

• Develop modular AI apps, RAG pipelines, and microservices integrated into enterprise Finance tools.
• Co-own codebases, repo standards, and infrastructure to reduce single points of failure.
• Maintain Dockerized deployments, CI/CD pipelines, API gateways, and vector stores with clean architecture.
• Implement real-time monitoring, logging, rate-limiting, and cost tracking; manage incident triage and operational support.
• Build ETL/ELT pipelines using SQL, dbt, and Python to ingest ERP data and unstructured documents into AI contexts.

Skills

AI Engineering

Python

SQL

Docker

CI/CD

API integrations

Cloud platforms

RAG frameworks

Vector databases

Communication skills

Tools

dbt

Job description

What Maintenance Training Manager Aviation Defense

Responsibilities

• Production Solution Development: Build, optimize, and deploy modular AI applications, RAG pipelines, and microservices integrated directly into enterprise Finance tools and databases.
• System Continuity & Keyperson Backup: Co-own codebases, repository standards, and infrastructure alongside the Senior Data Scientist to eliminate single-point-of-failure risks.
• MLOps, CI/CD & Infrastructure: Maintain Dockerized deployments, automated CI/CD pipelines, API gateways, and vector store instances using clean code architecture and automated testing.
• Production Support & Observability: Implement real-time monitoring, error logging, rate-limiting, and cost tracking (token usage, latency optimization), while managing routine incident triage and operational support.
• Data Integration: Engineer robust ETL/ELT pipelines using SQL, dbt, and Python to ingest structured ERP/ledger data as well as unstructured documents into AI contexts.

What you will bring

• Typically 3+ years of hands-on experience in AI Engineering, Software Engineering, or Data Engineering building production-ready data or AI applications.
• Core Technical Stack: Python, SQL; experience with RAG frameworks, vector databases, Docker, CI/CD, API integrations, and cloud platforms.
• Strong communication and collaboration skills with the ability to work with both technical and non-technical stakeholders.