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Tier-1 brand but senior, niche agentic AI leadership reduces candidate density, yielding medium competition.
Highly specialized agentic AI, multi-agent orchestration, and enterprise cloud governance demand domain-specific experience.
Explicit 12–17 years and mandatory senior ML platform, multi-cloud, and governance requirements increase screening strictness.
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Own and set strategy for enterprise agentic AI platform architecture, multi-cloud scalability, governance, and security across AWS, Google Cloud, and Azure.
Lead engineering leadership talent development and drive innovation in multi-agent orchestration and platform resilience.
Represent agentic AI pods in executive governance, ensure platform-wide reliability, cost optimization, and compliance across cloud environments.
12–17 years of relevant experience including leadership of large-scale, multi-agent or AI-driven platforms.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Proficient in Python and familiar with at least one additional modern language (Java, Go, or C++).
Extensive hands-on and leadership experience with multi-cloud environments (AWS, Google Cloud, Azure), including security, governance, and cost optimization.
Demonstrated strategic ownership of large AI platform architecture and technology roadmaps with expertise in agentic AI systems.
Experienced in setting organizational standards for reliability, scalability, and incident management of AI systems in enterprise settings.
Proven ability to partner with executive and cross-functional teams and build engineering leadership talent while fostering innovation in cloud-native AI platforms.