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Mid-level AI operations role with common Python requirement and metro location increases applicant density.
Role requires AI-ops expertise and finance/PE context, so background portability across industries is limited.
Explicit 4+ years requirement plus mandatory Python and AI-ops domain skills increases filter strictness.
Monitor AI-driven workflows in production to detect abnormal behaviors, trust issues, and degraded outputs affecting finance-sensitive outcomes.
Investigate output-quality incidents, distinguishing software defects from model or data issues, and partner with Engineering, QA, and business teams on incident resolution.
Support operational controls including human-review patterns and vendor solutions, while acting as product owner for AI usage and adoption dashboards to track performance and adoption metrics.
4+ years experience in AI operations, business process operations, production support, analytics, or QA.
Proficiency in Python and experience utilizing APIs.
Bachelor's degree preferred but not strictly mandatory.
This position is not eligible for immigration sponsorship; US office-based with hybrid work flexibility.
Experienced in managing AI-enabled workflows in finance or high-trust environments, with strong analytical skills to assess nuanced workflow issues.
Ability to collaborate effectively across technical and non-technical teams under ambiguity and pressure, balancing evidence and business impact.
Experienced in product ownership or operational analytics roles involving cross-functional coordination and incident management.