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Tier-1 employer and Bangalore metro increase competition, though senior, specialized cloud+AI leadership limits generalist applicants.
Role requires deep cloud platform, AI assurance, and enterprise governance expertise, limiting cross-industry transferability.
Explicit 8+ years, 3+ years leadership, and mandatory GCP/AI platform expertise make filters stringent.
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Own end-to-end GCP cloud platform including landing zone, security, IAM, networking, and platform operations ensuring reliability and observability.
Lead design and architecture of autonomous AI agents and AI platform solutions on GCP and Google Agent Builder, translating business priorities into production-grade, cost-effective, and compliant agent roadmap.
Build and lead a multidisciplinary engineering team, embed AI assurance, data privacy, governance and responsible-AI controls to enable scalable, secure delivery of AI automation at enterprise grade.
8+ years in software, data, ML, or cloud engineering with at least 3 years of technical team leadership.
Strong hands-on expertise in GCP platform technologies including landing zone design, IAM, networking, security, Vertex AI/Agent Builder, and infrastructure-as-code (ideally Terraform).
Proven experience delivering production AI/ML or LLM-based solutions end-to-end with knowledge of agentic architectures and AI assurance frameworks.
Work Experience Required: 8+ years as stated; Notice Period: Not explicitly mentioned in the JD.
Experienced cloud engineering lead with demonstrated ownership of scalable, secure enterprise AI platform architecture and operations on GCP.
Proficient in embedding AI assurance, privacy (GDPR/UK GDPR compliance), and governance into AI product lifecycle within regulated, consumer-facing environment.
Strong at balancing rapid delivery with enterprise discipline, managing cross-disciplinary teams, stakeholder engagement, and delivering measurable AI automation value at scale.