Lead AI Ops Engineer

Posted Yesterday
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Gurugram, Haryana, IND
Hybrid
Expert/Leader
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
We are a global technology company in the payments industry.
The Role
Own production operations for AI agents, including monitoring, observability, evaluation, drift detection, incident triage, root-cause analysis, and reliability management. Partner with AI Engineering to test prompts, context, and routing changes, validate improvements, and support deployment. Embed responsible AI governance through approval workflows, audit logging, access controls, and policy enforcement while translating production signals into prioritized technical actions.
Summary Generated by Built In
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Lead AI Ops Engineer
AI Ops
Overview:
Mastercard's Operational Intelligence team is building the next generation of data products and AI solutions that help customers access and use operational insights in new ways. As AI agents move from POC to production, their behavior keeps changing in real time: the context they retrieve, the skills they select, how they resolve exceptions. These agents are never really "finished." They keep learning from production outcomes, so their reliability, safety, and trustworthiness need to be actively operated, not just monitored. That is the job of AI Ops: making sure each agent's reasoning stays correct, its context stays current, and its behavior stays governed as it learns.
Role:• Own end to end production monitoring for one or more AI agents, tracking key metrics, KPIs, accuracy, latency, SLA breaches, guardrail triggers, and out of scope rates through dedicated observability dashboards• Serve as L1/L2 production support, providing first response monitoring, triage, and escalation to tech teams as new agentic services go live• Identify and diagnose issues by monitoring eval scores and drift alerts, inspecting failing traces and patterns, and classifying root causes such as intent, tool, parameter, or hallucination errors• Evaluate whether the agent's reasoning remains correct in production, checking whether context retrieval stays current, whether resolutions match ground truth, and whether the learning loop is drifting• Monitor and manage post production reliability, including API and authentication failures and issues originating from external AI endpoints, to protect revenue generating, client facing agents• Partner with AI Engineering to prioritize fixes, run experiments on prompts, context, and routing in Dev, and validate improvements via evals before handing off proven changes for deployment• Embed governance within the agent's learning loop so that approval workflows and audit logging travel with every production change, rather than being added after the fact
All About You:• Experience monitoring or operating production AI/ML or agentic systems, including observability, evaluation, and drift detection practices• Strong analytical skills to diagnose root causes across intent classification, tool selection, parameter errors, and hallucination patterns• Understanding of AI/LLM observability concepts such as tracing, telemetry, guardrails, and evaluation engineering including benchmarks, automated evals, human review, and regression testing• Familiarity with governance, compliance, and responsible AI practices such as PII detection, access control, audit logging, and policy enforcement is a plus• Ability to work independently alongside existing Tech teams while owning a dedicated agent's post launch health• Excellent communication skills to translate production signals into clear, prioritized asks for AI Product and AI Engineering teams• Comfort working in a fast evolving environment where the process itself, not just the throughput, is what is being continuously operated on and improved
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
  • Abide by Mastercard's security policies and practices;
  • Ensure the confidentiality and integrity of the information being accessed;
  • Report any suspected information security violation or breach, and
  • Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

Skills Required

  • Experience monitoring or operating production AI, ML, or agentic systems
  • Experience with observability, evaluation, and drift detection practices
  • Strong analytical skills for diagnosing intent, tool selection, parameter, and hallucination errors
  • Understanding of AI/LLM observability, tracing, telemetry, guardrails, and evaluation engineering
  • Ability to work independently while owning post-launch health of AI agents
  • Excellent communication skills for translating production signals into prioritized requests
  • Familiarity with governance, compliance, and responsible AI practices, including PII detection, access control, audit logging, and policy enforcement

What the Team is Saying

Jenny
Mastercard

Mastercard Compensation & Benefits Highlights

  • Retirement Support — Retirement plans are highlighted as especially strong, featuring a notably generous company match and added financial-planning resources. Feedback suggests this component stands out as a key strength of the overall package.
  • Parental & Family Support — Parental and family benefits are consistently portrayed as robust, including extended new-parent leave and assistance for fertility, adoption, and surrogacy. Feedback suggests these programs are a signature part of the offering.
  • Leave & Time Off Breadth — Paid time off is described as substantial, with multiple leave types and generous vacation and personal days noted in U.S. materials. Feedback suggests time off is frequently praised as a differentiator.

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The Company
HQ: Purchase, NY
38,800 Employees
Year Founded: 1966

What We Do

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re building a resilient economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Why Work With Us

We live the Mastercard Way: creating value in the communities we touch, growing together through the opportunities we see, and moving fast to innovate and scale. Our collaborative culture and our passionate people are the key to what we do, driving meaningful change as one team and connecting everyone to priceless possibilities.

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In our ongoing workplace evolution, we’ve introduced hybrid work, Work-From-Elsewhere Weeks and Meeting-Free Days.

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