Own architecture and strategy for predictive intelligence services.
Drive unified architecture across services; reduce duplication.
Provide hands-on design and leadership for major features and platform initiatives.
Define MLOps strategy for training, deployment, and monitoring on Kubernetes across clouds.
Establish best practices for scalability, fault tolerance, observability, and ops.
Mentor senior engineers; partner with data scientists to improve quality.
Collaborate with Product/Data Science/Platform to shape the multi-quarter roadmap.
Represent AI engineering in technical discussions and architecture reviews.

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