Role & responsibilities

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.
- Robust stakeholder communication — comfortable presenting operational updates to senior Risk/Technology/AD- level stakeholders.

📌 Lead Analyst Manager (Pune)
🏢 Symphoni HR
📍 Pune