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Popular cloud/infrastructure role with broad requirements and metro location increases competition.
Specialized enterprise AI infrastructure experience is somewhat limiting but still transferable across tech-focused employers.
Explicit 8-10 years plus senior enterprise AI infrastructure and architecture requirements tightly filter candidates.
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Own end-to-end technical architecture, design, and implementation of enterprise-grade AI systems across application, hardware, platform, network, and infrastructure layers.
Lead technology evaluation via Proofs of Technology (POTs) and Proofs of Concept (POCs) to validate solution compatibility and performance.
Collaborate across multiple engineering teams and with customers to translate business needs into scalable, secure, and reliable AI solutions.
8-10 years of experience in enterprise AI solution architecture or related roles.
Strong technical depth across AI applications, infrastructure, platforms, hardware, networking, and deployments.
Demonstrated skills in capacity planning, reference architecture design, and evaluation of technology stacks through POCs/POTs.
Mandatory customer-facing experience with stakeholder management and ability to guide multi-disciplinary engineering teams.
Experienced leader with proven ability to coordinate multiple engineering disciplines in delivering complex enterprise AI platforms.
Deep understanding of enterprise-grade quality attributes such as security, scalability, and reliability in AI environments.
Proficient in assessing existing technical debt and designing optimized solutions that work within complex customer ecosystems.