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Job Description
Structured overview of role & requirementsAbout This Role
Lead design and architecture of enterprise-scale AI platforms focusing on scalability, security, and operational readiness.
Define and implement frameworks for model lifecycle management, MLOps/LLMOps, and AI observability to enable robust deployment and monitoring.
Establish Responsible AI principles, governance frameworks, and drive reusable architecture standards for AI and GenAI solutions across teams.
Minimum Requirements
At least 6 years of experience in AI/ML engineering with hands-on expertise in enterprise-scale AI platform design and operationalization.
Advanced programming skills in Python and PySpark and experience with cloud-based AI platforms.
Proven knowledge in MLOps/LLMOps, AI observability, Responsible AI, and governance including model risk, security, and compliance.
Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related field.
Ideal Candidate Profile
Experienced leader in designing and operationalizing AI architectures at scale within enterprise environments.
Strong technical decision-maker skilled at defining reusable AI/GenAI architecture patterns and governance frameworks.
Technically proficient in advanced ML frameworks, pipeline orchestration tools (KubeFlow, BentoML), and AI observability with a focus on compliance and operational excellence.