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Senior, niche agentic-AI leadership in Bangalore reduces applicants, but strong AI demand and brand keep competition medium.
Agentic AI platform skills are transferable across industries, though financial compliance and enterprise governance slightly increase domain specificity.
Explicit 12–17 years requirement, deep agentic AI, multi-cloud, and leadership mandates make filters highly stringent.
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Own the enterprise agentic AI platform strategy, architecture, technology roadmap, and governance standards across multi-cloud environments (AWS, Google Cloud, Azure).
Lead engineering leadership talent and drive innovation in multi-agent orchestration, security, and operational resilience at scale.
Represent and influence platform strategy in executive and cross-functional governance forums focusing on platform reliability, scalability, cost optimization, and compliance.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field; advanced degrees a plus.
12–17 years of experience including leadership of large-scale, multi-agent or AI-driven platforms.
Proficiency in Python and familiarity with at least one additional modern programming language (e.g., Java, Go, C++).
Extensive hands-on leadership experience with multi-cloud (AWS, Google Cloud, Azure) environments covering security, governance, and cost optimization.
Proven strategic ownership of agentic AI platform architecture and technology roadmaps with focus on multi-cloud scalability and governance.
Experienced in building and developing engineering leadership teams and fostering innovation in cloud-native AI platforms.
Skilled in collaborating with executive and cross-functional teams on platform delivery, compliance, risk management, and organizational standards.