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Tier-1 brand, metro location, and mid-level ML role with general appeal create medium competition.
Requires payments and regulated-finance ML experience, reducing cross-industry transferability.
Explicit 6+ years requirement plus mandatory ML, MLOps, RAG and payments skills increases strictness.
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Design, build, and operationalize AI/ML solutions focusing on anomaly detection, fraud indicators, and operational risk in high-volume payment flows.
Develop and deploy scalable data pipelines and AI systems using Generative AI, RAG, and agentic AI in a regulated financial services environment.
Implement MLOps practices, manage AI governance, explainability, and partner cross-functionally to translate business requirements into AI-enabled controls.
6+ years of professional experience with 3–5 years in Data Engineering, AI Engineering, or related disciplines.
Bachelor's or Master's degree in Computer Science, AI/ML, or related field.
Proficiency in Python, SQL, APIs, workflow automation, cloud-native architectures, and experience with MLOps, Docker, Kubernetes.
Experience with Generative AI, Retrieval-Augmented Generation (RAG), vector databases, and integrating LLMs with external systems.
Experienced in building anomaly detection and fraud detection models using diverse machine learning techniques applied to payments data.
Comfortable working in a regulated financial services setting with emphasis on governance, explainability, and risk management for AI solutions.
Capable of collaborating closely with cross-functional teams including payments operations, risk, compliance, cybersecurity, and engineering.