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Recognizable brand and metro location increase competition, though senior specialized role moderates applicant density.
Platform and AI operationalization skills are moderately transferable across industries.
Explicit 10+ years plus mandatory platform/DevOps/cloud expertise makes hiring filters highly rigid.
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Lead architecture and engineering of enterprise AI platform to deliver secure, scalable, reusable AI services.
Own productization of foundational AI capabilities such as AI Gateway, Semantic Layer, Agentic Harness, CLI tooling, and integration frameworks.
Define and execute platform engineering strategy including CI/CD, IaC, API lifecycle, observability, security, governance, and multi-environment deployment.
Bachelor's or Master's degree in Computer Science, Data Sciences, or related fields.
10+ years experience in platform engineering, cloud architecture, DevOps/SRE, or software engineering.
Expertise in CI/CD, Infrastructure as Code, cloud-native architectures, API platforms, security, automation, and operationalizing AI/ML or GenAI platforms in enterprise contexts.
Work Experience Required: 10+ years in relevant engineering roles.
Experienced in building and scaling large-scale enterprise AI or platform engineering solutions with developer enablement focus.
Strong knowledge of cloud architecture, automation, and best practices for AI/ML platform operationalization.
Comfortable working across multiple functional teams to set engineering standards, reference architectures, and drive organizational adoption of AI platform services.