The Cloud Centre of Excellence (CCOE) team within Digital Technology is looking to design and build infrastructure and platform features to support AI workloads, focusing on creating scalable, reliable systems, automating processes, and delivering user-friendly software that aligns with customer needs.
Requirements
- 3+ years of development experience with languages like Python, Go, Java, or similar.
- Advanced expertise in JavaScript, modern UI frameworks, and REST API development.
- AI or Machine Learning implementations are required.
- 3+ years of hands-on experience in infrastructure, platform operations, deployments, and DevOps practices.
- Familiarity with DevOps tools such as Helm, Terraform, Kubernetes, Docker, Splunk, and Jenkins.
- Experience with software-defined networking, infrastructure as code, and configuration management.
- Hands-on experience with any one of the major Cloud platforms like Microsoft Azure, Google Cloud (GCP), or Amazon Web Services (AWS).
Responsibilities
- Play a key role in designing, developing, and implementing infrastructure, platform, deployment, and observability features that support AI workloads.
- Work closely with researchers, AI engineers, and infrastructure teams to ensure the performance, scalability, and reliability of Kubernetes clusters.
- Contribute to the design and development of new automation solutions and features.
- Write high-quality, clean, and reusable code by adhering to best practices in software architecture and engineering processes (e.g., Code Reviews, Unit Testing).
- Partner with product owners to fully understand requirements, and take ownership of your code from design through implementation, test automation, and final product delivery.
- Build software that is intuitive and user-friendly, enabling customers to easily extend and customize functionality to meet their unique needs.
Other
- Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving.
- Proven experience in driving large-scale deployments for enterprise clients, especially with AI-based products.
- Ability to lead projects with significant technical risk and deliver successful outcomes.
- Strong team collaboration skills, attention to detail, and the ability to communicate effectively with others.
