Lead Analyst – AI Ops Support

Crisil; Chennai; Presencial; INR 3.000.000 - 5.000.000; Jornada completa

Descripción de la vacante

Crisil in Chennai (preferred) / Pune seeks a Lead Analyst for AI Operations in the Counterparty Credit Risk Technology team. You will lead offshore AI Ops support, monitor production, and automate AI-enabled controls across CCR exposure and risk reporting pipelines.

The role demands 8–10 years in tech ops, with 3–4 years in AI/ML ops, offshore/onshore leadership, and strong stakeholder communication to coordinate with Risk, Model Risk and Technology teams.

Formación

• 8–10 years in technology operations / production support.
• 3–4 years in AI Ops, MLOps or AIOps-adjacent capacity.
• Experience monitoring AI/ML models in production.

Responsabilidades

• Own end-to-end production monitoring of AI/ML-enabled processes across the CCR technology team.
• Track model performance, drift, and output anomalies; define thresholds and alerts.
• Lead automation roadmap for AI Ops tooling and self-healing workflows.
• Primary interface between AI Ops, Model Risk, Data Science and Engineering on production issues.

Conocimientos

AI Ops

Production monitoring

Model performance

Drift detection

Alerting tooling

Stakeholder comms

Team leadership

CCR concepts

Herramientas

Dashboards

Alerting platforms

Log/metrics analytics

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.