AI Software Engineer

AI Software Engineer at Commonwealth Bank

You are an AI guru who gets a buzz from integrating AI solutions that drive real-time decision-making. We are looking for Software Engineers and Senior Software Engineers to be part of Australia’s largest digital transformation using AI technologies. Together we can reimagine banking, transforming how we serve customers, colleagues, and communities.

See yourself in our team

We are looking for innovative AI Solutions Engineers to join our AI Enablement function within Business Bank. In this role, you will integrate AI models into business processes, focusing on building APIs, scaling model scoring functions, and managing scalable data access patterns for both batch and real-time AI use cases—covering both traditional and generative AI. You will leverage cloud platforms, containerization, and CICD practices to ensure secure, scalable, and efficient AI solutions.

Do work that matters

This role is ideal for engineers with experience in building large scale applications using C#, Python, or Java and who thrive on solving complex business problems using advanced AI tools.

Key Responsibilities:

• API Development & Integration: Design, build, and integrate APIs that provide seamless access to AI models across business processes, ensuring efficient data flow and usability.
• Model Scoring & Scaling: Develop scalable model scoring functions that handle high-volume, low-latency AI requests, ensuring models perform effectively across batch and real-time use cases.
• Scalable Data Access Patterns: Design and implement robust data access patterns for both batch and real-time AI processes, enabling optimal performance for traditional machine learning and generative AI models.
• Prompt & Chunk Management for Generative AI: Manage and optimize the flow of data chunks and prompts for generative AI models to enhance output quality and ensure integration with business applications.
• Cloud Integration: Deploy AI models on cloud platforms, ensuring they are scalable, secure, and cost-efficient, supporting both batch and real-time workloads.
• Containerization: Utilize containerization technologies such as Docker and Kubernetes for scalable, secure model deployment and orchestration in cloud environments.
• CICD Pipeline Implementation: Build and maintain CICD pipelines for the continuous integration, testing, and deployment of AI models and APIs, ensuring a streamlined and automated development process.
• Problem Solving & Optimization: Collaborate with cross-functional teams to solve complex business challenges through the integration of scalable AI solutions, improving business outcomes.
• Collaboration & Coordination: Work with data scientists, engineers, and business stakeholders to ensure AI models are successfully integrated and aligned with business goals.
• Security & Compliance: Ensure that all AI models and solutions meet internal security requirements and comply with industry regulations, particularly in the banking sector.

Tech Skills

We don't expect you to know everything, but experience in the following will set you up for success:

• Strong experience in building and integrating APIs to facilitate AI model access within business processes.
• Proficiency in C#, Python, or Java, with experience developing scalable AI solutions.
• Hands-on experience with cloud platforms (AWS, GCP, Azure) for AI deployment and integration, supporting both batch and real-time data processing.
• Expertise in scalable data access patterns for both batch and real-time AI models, particularly in generative AI use cases.
• Proficiency in containerization technologies (Docker, Kubernetes) for scalable, secure AI deployments.
• Experience setting up CICD pipelines for automating the deployment and testing of AI models.
• Strong problem-solving skills, with a focus on creating scalable solutions that deliver business impact.

We’d love to hear from people who are:

• Experienced within the banking or financial services industry, particularly with AI integration projects.
• Familiar with data pipeline and processing tools like Apache Kafka, Spark, or similar.
• Knowledgeable in AI governance, risk management, and compliance frameworks in regulated environments.

Key skills/competency

• AI Integration
• API Development
• Cloud Platforms (AWS, GCP, Azure)
• Containerization (Docker, Kubernetes)
• CICD Pipelines
• Generative AI
• Machine Learning
• Scalable Data Access
• C#, Python, Java
• Security & Compliance