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Tier-1 employer and Bangalore location increase competition, but senior, niche agentic AI-data expertise reduces applicant density.
Requires deep enterprise data and analytics career experience, reducing cross-industry transferability.
Explicit 10+ years plus 3+ years AI and platform requirements enforce strict filters.
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Architect AI-ready data foundations enabling use by LLMs and agentic workflows, including semantic and context layers.
Lead technical workstreams end-to-end, setting direction and owning deliverables across cross-functional teams.
Build hands-on AI solutions with LLMs and collaborate with AI vendors and business stakeholders to prototype and scale architectures.
10+ years in enterprise data warehousing, data modeling, engineering, and architecture with Data & Analytics as core career focus.
4-year or Graduate Degree in Computer Science, Information Systems, or related field, or equivalent work experience.
3+ years hands-on experience building production-grade AI solutions with LLMs; pilots/proofs alone not sufficient.
Experience with Databricks and Microsoft Fabric strongly preferred; familiarity with Azure and AWS data ecosystems expected.
Experienced technical leader capable of setting and owning architectural strategy in ambiguous, high-stakes environments.
Broad enterprise domain knowledge across multiple business functions to connect data architecture to business outcomes.
Demonstrates both strategic communication skills with executives and hands-on technical expertise building AI-driven data solutions.