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Tier-1 brand, visible ML/AI role in metro attracts many qualified candidates.
Specialized AI, MLOps, and enterprise governance needs make candidate skills less transferable across industries.
Extensive mandatory technical skills, enterprise MLOps, cloud, and leadership imply high shortlisting strictness.
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Lead design, architecture, and implementation of enterprise-scale AI and Generative AI platforms and solutions.
Own technical vision and standards for AI engineering, establish MLOps/AgenticOps and cloud-native AI infrastructure.
Provide technical leadership and mentorship to multidisciplinary AI engineering teams, collaborating with stakeholders to deliver scalable, secure AI capabilities.
Bachelor's or Master's degree in Computer Science, AI, Software Engineering or related field.
Extensive experience in designing, developing, and deploying enterprise-scale AI/ML solutions in production.
Proven experience leading technical teams on complex software engineering initiatives.
Strong software engineering skills in Python; expertise with cloud platforms (AWS, Azure, GCP), distributed systems, microservices, Kubernetes, containerization, and enterprise MLOps/AgenticOps.
Experienced AI engineer with a strong background in production deployment and lifecycle management of advanced AI including Generative AI (LLMs, RAG, vector DBs).
Skilled technical leader comfortable setting architecture governance and driving enterprise AI adoption across multifaceted teams.
Focused on building scalable, secure, compliant AI systems with responsibility for operational excellence and innovation at enterprise scale.