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Tier-1 brand, metro location, popular AI role, and broad required skills create high competition.
Core applied AI engineering skills transfer across industries, but enterprise payments and compliance raise fit sensitivity moderately.
Principal-level production ML/LLM deployment, security, and responsible AI requirements make hiring filters stringent.
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Lead design and development of AI-based production applications integrating machine learning and generative AI within Mastercard’s AI ecosystem.
Integrate, operationalize, and maintain ML, deep learning, or LLM models in APIs, services, workflows, and user interfaces with attention to model versioning, deployment, monitoring, and updates.
Implement AI guardrails including bias mitigation, explainability, security, privacy, compliance, and ethical AI, while mentoring team members on best practices and emerging AI trends.
Experience deploying production-grade AI applications with ML, deep learning, or LLMs including operationalization and monitoring.
Strong software engineering skills in languages such as Python, Java, or C#.
Familiarity with cloud platforms like AWS, Azure, or GCP and containerized deployments.
Work Experience Required: Not explicitly mentioned in the JD.
Advanced expertise integrating generative AI, LLMs, prompt engineering, and RAG architectures into business applications.
Strategic thinker with experience advising and shaping AI roadmaps and technology adoption in complex environments.
Experience working and leading with global teams and communicating effectively with senior leaders and executives.