AI Operations Analyst

Roles and Responsibilities :

• AI / ML Operations (core focus)
–Monitor AI/ML-enabled operational processes daily; flag drift, anomalies and output-quality degradation against defined thresholds.
–Perform first-line investigation of model/data anomalies and route to the correct owner (Model Risk, Data Science, Engineering, Risk).
–Support the human-review and escalation workflow for AI-flagged exceptions, maintaining a clean audit trail.
–Contribute to tuning of alerting logic and thresholds as model behaviour and data patterns evolve.
• Automation & Tooling

–Build and maintain automated alerts, dashboards and scripts that reduce manual monitoring and reconciliation effort.
–Identify recurring manual tasks and propose/build automation, working with the Lead Analyst to prioritize.
–Maintain and enhance existing automation/scripts as upstream systems and data feeds change.
• Monitoring & Incident Support
–Monitor batch, interface and application health for CCR/exposure systems; investigate exceptions within SLA.
–Support incident management: log, triage severity, coordinate with Engineering, and contribute to RCA for recurring issues.
–Track and report incident/SLA metrics for the processes owned.
• CCR & Risk Context (supporting knowledge)
–Apply working understanding of exposure, EPE/PFE, limits and collateral concepts to sense-check monitoring outputs and reconciliation breaks.
–Review trade, market-data, counterparty and collateral reconciliation breaks between upstream and downstream systems as part of anomaly triage.
• Governance & Team Support
–Maintain SOPs and runbooks for the processes owned; keep control evidence audit-ready.
–Mentor and quality-check the work of Analysts; support onboarding and cross-training.

Job Requirements :

• 1–10 years in technology operations / production support; prior exposure to AI Ops, MLOps or intelligent-automation environments preferred.
• Comfortable working with monitoring/observability and dashboarding tools and able to build and maintain alerting logic.
• Working knowledge of Counterparty Credit Risk concepts (EPE/PFE, exposure, limits, collateral) sufficient to prioritize alerts independently.
• Strong analytical and RCA skills; comfortable working to SLA in a production-support environment.
• Ability to mentor junior team members and communicate clearly with cross-functional stakeholders.