AI Platform Engineering - MLOps/DevOps

Design scalable, secure, and reliable infrastructure to support AI/ML workloads Build and implement MLOps pipelines to streamline model development, testing, and deployment Manage the end-to-end lifecycle of ML models, from development through retirement Set up monitoring and observability systems to track model performance, drift, and health in production Implement governance controls to ensure AI systems are compliant, auditable, and responsibly managed Integrate AI/ML platforms and models with existing enterprise systems and workflows Requirements 6+ years of relevant experience in AI platform engineering, MLOps, or DevOps roles Strong hands-on experience in AI infrastructure architecture and design Proven expertise in MLOps implementation and CI/CD pipelines for ML Solid understanding of model lifecycle management practices Experience with model monitoring and observability tools and frameworks Familiarity with AI governance controls and compliance requirements Experience with integration with enterprise systems (APIs, data pipelines, cloud platforms)