Job Description

Role Summary We are seeking a senior Enterprise Architect to lead the design of cloud-native MLOps and data platforms on AWS. This role is focused on enterprise-scale architecture, platform design, and governance of the ML lifecycle—not model development or pipeline implementation. The ideal candidate brings deep expertise in AWS cloud architecture and MLOps platform design, with the ability to define reference architectures, standards, and scalable patterns that enable multiple teams to build and operate machine learning solutions in a secure, compliant, and repeatable manner. Key Responsibilities Define and lead enterprise MLOps architecture across the full ML lifecycle: data ingestion, feature engineering, training, validation, deployment, monitoring, and retraining Design cloud-native reference architectures on AWS for ML platforms and data-driven applications Establish standards and governance for: model lifecycle management (versioning, lineage, approvals) reproducibility and environment standardization responsible AI and auditability Architect scalable ML inference solutions using microservices and event-driven patterns (batch and real-time) Define CI/CD patterns for ML and integrate with enterprise DevOps tooling Partner with business and engineering teams as a trusted advisor to translate requirements into scalable architectures Lead cloud adoption and modernization strategies, including AWS landing zones and multi-account design Collaborate with Security, Risk, and Compliance teams to ensure secure-by-design and compliant architectures Produce architecture artifacts (reference architectures, diagrams, roadmaps) Required Experience 12+ years of experience in software engineering, data platforms, or cloud architecture 5+ years as a Solution or Enterprise Architect in AWS environments