Design and implement end-to-end AI workflows across teams.
Connect data platforms, AI models, and internal apps into production-grade solutions.
Ensure AI deployments are scalable, secure, and compliant across regions.
Define enterprise AI roadmap aligned to business priorities.
Build internal AI capability through enablement content and trainings.
Track usage, performance, and ROI; report to executive leadership.

🎯 Requirements

10–15 years in tech/engineering/architecture with AI/ML exposure.
Deep knowledge of LLMs, agentic frameworks, RPA, vector databases.
Cybersecurity principles to address data risk in AI deployments.
Executive communication to translate AI concepts for leadership.
Experience driving enterprise change across multi-country contexts.
Proven ability to quantify business value from technology initiatives.

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