AI Operations Engineer

Job no: 495055
Work type: Full-time
Location: Sydney - CBD
Categories: Business Innovation, Information Technology

Credit Corp is Australia's largest provider of sustainable financial services to the credit impaired consumer segment. We are an ASX listed company with over 2200+ staff in multiple locations in Australia, USA, New Zealand and Philippines. We work closely with regulators to provide sustainable financial solutions with the objective of improving our customers' circumstances as a pathway to mainstream financial inclusion.

The Role:

We're seeking an experienced AI Operations Engineer who is passionate about building reliable, scalable systems that enable AI at scale. You're someone who thinks operationally-not just in code-and understands that great AI products require more than just good models; they require robust infrastructure, meticulous monitoring, and disciplined incident management. You should be detail-oriented and methodical, comfortable working in ambiguity, and thrive in a collaborative environment.

Most importantly, you're eager to grow as we scale our AI capabilities. Credit Corp is at an exciting inflection point in our AI journey. We currently have our first AI products in production serving real customers, and we're executing an ambitious roadmap to expand our AI capabilities across multiple business units and product lines. This is the critical phase of establishing robust operational foundations that will support significant growth. In this role, you'll have the unique opportunity to shape how we operationalize AI across the organization and establish the best practices and processes that will serve us for years to come-essentially building the operational playbook for Credit Corp's AI future.

You will have:

• Exceptional communication skills
• 5+ years MLOps/DevOps/SRE experience - with demonstrated success in deploying and managing AI/ML models in production environments
• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or related field
• Cloud-native ML platforms - particularly GCP and Vertex AI, including model deployment, scaling, and infrastructure management
• DevOps engineering practices - CI/CD pipelines, infrastructure-as-code, containerization (Docker), orchestration (Kubernetes), and automation scripting (Python/bash)
• Monitoring and observability - comprehensive systems for production AI/ML services, including model performance tracking, data drift, and system health metrics
• ML governance frameworks - model versioning, compliance requirements, and operational best practices for regulated environments
• Data quality and streaming - monitoring frameworks, data validation tools, event-driven architectures, and real-time data streaming patterns
• Regulated industry experience - particularly financial services (highly desirable)
• Excellent organisation and time management skills

In order to be successful in this role you will be driven, highly motivated and eager to learn.

If you're looking for an opportunity to work for a financial services organisation which offers growth and development and has a great culture, then this is the role for you.