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Senior, niche AI-architecture role at a notable enterprise platform in a metro city yields moderate competition.
Deep learning, MLOps, and enterprise-scale architecture needs make industry background highly relevant and less transferable.
Explicit 10+ years plus 5+ years ML specialization and required architecture/MLOps expertise makes shortlisting highly strict.
Own and evolve the end-to-end architecture of a large-scale enterprise AI platform focusing on scalability, reliability, security, and cost efficiency.
Lead implementation of scalable, secure data pipelines and production deployment of deep learning and AI systems with best-practice MLOps, including CI/CD, model monitoring, and drift detection.
Provide principal-level technical leadership by mentoring senior engineers, guiding architecture/design reviews, and setting engineering standards across teams.
10+ years in software architecture and large-scale production systems; 5+ years specializing in deep learning and data engineering.
Proficiency in Python and strong backend engineering with expertise in algorithms, data structures, distributed systems, and large-scale system design.
Experience with modern deep learning frameworks, agentic AI systems, and production lifecycle management of AI models.
Proven skills in building scalable data pipelines handling large volumes of structured and unstructured data with modern distributed computing frameworks.
Experienced in integrating AI, deep learning, and data engineering to architect enterprise-grade production platforms.
Capable of strategic architectural leadership influencing long-term platform direction and aligning technical solutions with complex business needs.
Comfortable working at the intersection of advanced AI, MLOps, and distributed systems technologies with a track record of mentoring senior technical staff.