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Specialized senior AI architect reduces applicant density despite metro location and recognizable corporate brand.
Specialized enterprise AI platform skills moderately transferable, with preference for regulated or large-organization experience.
Explicit 12–17 years and mandatory Generative AI, cloud architecture, and governance requirements make screening highly selective.
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Lead and own the enterprise-wide AI system architecture strategy for the full Generative AI platform stack, including shared services, orchestration, model integration, APIs, and downstream systems.
Define and govern reference architectures, design standards, cloud design principles, and integration patterns ensuring scalable, secure, resilient, compliant, and cost-effective AI platform operations across AWS, Azure, or GCP.
Chair architecture governance forums, make key architecture decisions, and represent Architecture in senior leadership and governance, aligning AI system designs with business priorities and regulatory requirements.
Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field; Master’s preferred.
12–17 years of experience in solution, enterprise application, platform, or AI/ML architecture with leadership of large-scale enterprise projects.
Deep expertise in Generative AI, LLMs, ML systems, RAG, vector databases, prompt orchestration, and AI platform integration.
Proven experience designing enterprise-scale AI architectures and cloud solutions on AWS, Azure, or Google Cloud with strong knowledge of AI governance, compliance, security, and DevSecOps.
Experienced leader comfortable engaging senior executives and cross-functional teams to drive architecture strategy and decisions.
Strong technical background in cloud-native AI/ML architectures including platform engineering, microservices, API integration, and distributed system design.
Skilled at balancing architecture innovation, compliance, operational stability, and cost efficiency within large, regulated enterprise contexts.