Lead Analyst – AI Ops Support

Crisil; Maharashtra; Presencial; INR 4.000.000 - 7.000.000; Jornada completa

Descripción de la vacante

Crisil is seeking a Lead Analyst to head the offshore AI Ops Support for the Counterparty Credit Risk Technology team. You will oversee production monitoring of AI/ML processes and drive automated monitoring, alerting, and issue resolution.

You will manage a small team of 3–4 analysts (Senior/Junior), coordinate with Risk, Model Risk and Technology stakeholders, and aim to reduce manual touchpoints while ensuring robust risk controls. Chennai (preferred) / Pune.

Formación

• 8–10 years in technology operations / production support with 3–4 years in AI Ops or MLOps.
• Experience monitoring AI/ML models in production and handling alerts.
• Exposure to AI Ops observability tooling and dashboards.

Responsabilidades

• Own end-to-end production monitoring of AI/ML-enabled processes across the CCR tech team.
• Track model performance, drift, data-quality degradation and alert thresholds with Model Risk and Data Science.
• Establish human-in-the-loop review for AI-flagged exceptions.
• Own the AI Ops tooling roadmap: monitoring, anomaly detection, self-healing workflows.
• Interface between AI Ops, Model Risk, Data Science and Engineering on production issues.
• Drive automation backlog and build dashboards, automated alerts, and investigate tools.

Conocimientos

AI Ops

Production monitoring

Model performance

Stakeholder comms

Team leadership

Herramientas

Observability tooling

Dashboards & alerts

Descripción del empleo

Job Description

Lead Analyst — AI Operations Support Team, Counterparty Credit Risk Technology

Lead Analyst – AI Ops Support

Experience

8–10 years

Location

Chennai (preferred) / Pune

Team size managed

3–4 analysts (Senior/Junior)

ROLE PURPOSE

Lead the offshore AI Ops Support function for the client's Counterparty Credit Risk (CCR) Technology team. The role is primarily an AI/ML operations role owing production monitoring, performance and active oversight, and automation of AI-enabled controls across CCR exposure, EPE/PFE and risk-reporting pipelines. A working knowledge of CCR concepts is a mandatory enabler, not the core of the job - required so the lead can correctly interpret alerts, detect false positives from genuine risk issues, and hold credible conversations with Risk, Model Risk and Technology stakeholders.

KEY RESPONSIBILITIES

• AI / ML Operations (core focus)
  • Own end-to-end production monitoring of AI/ML-enabled operational processes across the CCR technology team.
  • Track model performance, drift, data-quality degradation and output anomalies; define thresholds and alerting logic in partnership with Model Risk and Data Science.
  • Establish human-in-the-loop review and escalation protocols for AI-flagged exceptions.
  • Own the AI Ops tooling roadmap for the team: predictive monitoring, anomaly detection, automated prioritization and self-healing workflows.
  • Act as the primary interface between AI Ops, Model Risk, Data Science and Engineering on all model-related production issues.
• Automation & Continuous Improvement
  • Drive a team-wide automation backlog: automate manual monitoring, reconciliation and exception-management activities currently done manually.
  • Build and maintain dashboards, automated alerts and AI-assisted investigation tools; measure and report reduction in manual touchpoints and operational risk.
  • Prioritize and sequence automation initiatives against incident trends and MTTR data.
• Incident & Problem Management
  • Primary escalation point for high-severity incidents across CCR applications and AI-enabled processes.
  • Lead root-cause analysis for recurring calculation, data and model issues; own the permanent-fix backlog with Engineering.
  • Track incident volumes, SLA breaches, MTTR and recurring-problem trends; report on operational health.
• CCR & Risk Context (supporting knowledge)
  • Apply working knowledge of exposure, EPE/PFE, limits and collateral/margin concepts to correctly interpret monitoring alerts and data breaks.
  • Coordinate investigation of exposure/data discrepancies with Risk and upstream/downstream technology teams, as an input to the AI Ops response, not the primary workstream.
• Governance, Team Leadership & Stakeholder Management
  • Maintain SOPs, runbooks, escalation matrices and control evidence for audit and model-governance requirements.
  • Manage work allocation, quality review, KPIs and cross-training across the analyst team.
  • Provide regular operational health and improvement reporting to clients and other senior stakeholders.

REQUIRED SKILLS & EXPERIENCE

• 8–10 years in technology operations / production support, with at least 3–4 years in an AI Ops, MLOps or AIOps-adjacent capacity.
• Demonstrated experience monitoring AI/ML models in production — performance, drift, anomaly detection, human-review workflows.
• Hands-on exposure to AI Ops/observability tooling (e.g. dashboards, alerting platforms, log/metric analytics; specific tool stack per client environment).
• Solid grounding in Counterparty Credit Risk concepts (EPE/PFE, exposure, limits, collateral) enough to independently prioritize whether an alert is a data, model or genuine risk issue.
• Prior team-lead or people-management experience in an offshore/onshore delivery model.
• Strong stakeholder communication — comfortable presenting operational updates to senior Risk/Technology/AD-level stakeholders.