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Metro locations and engineering title increase applicants, but senior niche AI platform skills moderate competition.
Specialized AI platform and LLMOps skills are transferable across industries, but regulated-industry experience increases fit sensitivity.
Multiple explicit years and mandatory platform, cloud, and LLMOps skills enforce strict candidate filters.
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Lead architecture and design of a comprehensive enterprise AI platform covering Experience, Control, and Execution planes.
Define platform standards, build reusable AI platform capabilities, and solve complex engineering challenges to enable enterprise AI adoption.
Drive production operations and integration of AI and agentic technologies ensuring governance, observability, and optimized workflows.
7+ years of AI Platform Engineering experience.
3+ years experience designing cloud-native distributed platforms.
3+ years experience architecting AI/ML or GenAI platforms.
Experience with AWS EKS / Kubernetes and infrastructure as code tools like Terraform.
Proven ability as a hands-on architect for enterprise-grade AI platform capabilities across multiple platform layers.
Experience building Control Plane architectures and enterprise-scale AI governance frameworks.
Familiarity with production GenAI workloads and AI platform operations in regulated industries.