What you'll be doing

• Architect, build, and diagnose multi-tenant AI platform systems
• Work closely with AI application teams to design seamless workflows for continuous model training, inference, and monitoring
• Collaborate with AI experts to understand workflows, identify inefficiencies, and inform new platform features
• Engage with open-source communities and AI teams to develop a cohesive MLOps experience
• Design CI/CD automation frameworks that meet regulatory requirements
• Develop cloud-native deployment patterns for AI systems across environments
• Troubleshoot and debug user issues
• Provide operational and user-facing documentation

Requirements

• Proven experience with object-oriented programming languages such as Python or Go
• Experience designing cloud-native, distributed platforms
• Strong knowledge of Kubernetes, Argo, and container orchestration technologies
• Experience with modern CI/CD tools and GitOps workflows
• Familiarity with automation in model development lifecycles
• Proactive mindset and ability to collaborate with peers, stakeholders, and management
• Degree in Computer Science, Engineering, Mathematics, or related field, or equivalent work experience
• Understanding of computer science fundamentals such as data structures and algorithms