AIops Lead

Bupa; Gurugram District; On-site; INR 300,000 - 540,000; Full time

Job summary

Bupa is seeking a leader to drive AI-powered agentic capabilities across incident triage and service health. You will own the TOC strategy, roadmap, and release approach, designing human+AI workflows with clear reasoning and auditability to ensure reliable operation in live services.

The role emphasizes observability, telemetry quality, and integration patterns across hybrid environments, with a focus on measurable improvements in reliability and customer impact.

Qualifications

• Experience in AI engineering and agentic systems to improve live service outcomes.
• Strong observability, telemetry, and event management for operational data quality.
• Experience introducing AI, automation, or AIOps into operational environments safely and measurably.

Responsibilities

• Lead design, build, and operationalisation of agentic AI capabilities for event correlation, incident triage, service health assessment, knowledge retrieval, decision support, and bounded remediation.
• Own the product strategy, roadmap, backlog, release approach, and value measures for the TOC agentic capability.
• Design human + AI workflows with clear reasoning, planning, tool use, memory, identity, traceability, and auditability.
• Apply engineering judgement on code-first, low-code, multi-agent, and integration patterns based on risk and value.
• Ensure AI capabilities are measurable, production-ready, and safe to operate in live service environments.

Skills

AI engineering

Agentic systems

Automation

Observability

Incident management

Stakeholder leadership

Tools

ServiceNow

Google Cloud

Gemini Enterprise Platform

Python ADK

Cloud Run

Apigee

BigQuery

Vertex AI

AlloyDB

GCS

API mediation

Job description

The candidate will have responsibilities across the following functions:

AI Engineering, Agentic Capability and Product Leadership:

• Lead the design, build, and operationalisation of agentic AI capabilities for event correlation, incident triage, service health assessment, knowledge retrieval, decision support, and bounded remediation.
• Own the product strategy, roadmap, backlog, release approach, and value measures for the TOC agentic capability.
• Design human + AI workflows with clear reasoning, planning, tool use, memory, identity, traceability, and auditability.
• Apply strong engineering judgement on code-first, low-code, multi-agent, and integration patterns based on risk, scale, control, and operational value.
• Ensure every AI capability is measurable, supportable, production-ready, and safe to operate in live service environments.
• Drive event-driven operations by treating logs, alerts, events, traces, service state, and customer impact signals as first-class operational data.
• Improve telemetry quality, signal ownership, service mapping, dependency data, and operational context so AI and humans can reason from reliable evidence.
• Create decision-oriented views that show what is at risk, what is credible, what action is safe, and what customer or business impact is likely.
• Use operational data to identify reliability trends, leading indicators, toil reduction opportunities, and commercial or business impact where relevant.

TOC Strategy, Operating Model and Service Design:

• Define the TOC agentic strategy and operating model, covering authority, workflows, incident handling, roles, governance, and execution boundaries.
• Establish the TOC as an event-driven control plane for live operational risk and customer-impacting technology events.
• Create a phased roadmap from MVP to scale, proving value early and building confidence for wider adoption.
• Clarify where TOC capability starts and stops, keeping product, platform, infrastructure, and support team accountability explicit.
• Use AI, automation, and operational context to improve incident detection, triage, escalation, recovery, and root cause learning.
• Reduce alert noise, duplicated effort, manual triage, and avoidable operational toil.
• Ensure the capability works across hybrid environments, including legacy platforms, cloud services, SaaS, networks, booking, and clinical systems where in scope.
• Build credibility by demonstrating measurable improvements in live service outcomes, not just prototypes.
• Create strong collaboration with product and domain owners so telemetry, automation, and delegated authority are used without weakening team accountability.
• Build the internal skills, standards, support model, and run-operate-improve disciplines needed to sustain the capability.
• Link roadmap priorities to measurable improvements in service reliability, operational effectiveness, and business impact.

Requirements:

• Experience in AI engineering, agentic systems, automation, and observability, with a track record of applying these capabilities to improve live service outcomes.
• Strong understanding of observability, telemetry, event management, service mapping, operational data quality, and the use of signals to support decision-making. Job Description.
• Experience introducing AI, automation, or AIOps capability into operational environments in a way that is safe, measurable, supportable, and adopted by users.
• Credibility in live-service environments, with enough Technology Operations knowledge to understand incidents, hand-offs, escalation, service continuity, and operational risk.
• Strong stakeholder leadership and communication skills, with the ability to influence senior leaders, engineers, operators, control functions, and suppliers.
• Experience building or leading multidisciplinary teams through transformation, ambiguity, and organisational change.

Particularly Relevant Experience:

• Experience with ServiceNow as the operational system of record, including incident and workflow integration.
• Experience with Google Cloud or comparable cloud platforms used for agentic and data workloads, including familiarity with patterns such as Gemini Enterprise Agent Platform, Python-based ADK development, Cloud Run services, managed or proxied MCP access, Apigee, BigQuery, Vertex AI, AlloyDB, GCS, and secure API mediation.
• Experience operating in regulated or high-control environments where resilience, auditability, customer impact, and control discipline are critical.