AI Operations Analyst

At Zimmer Biomet, we believe in pushing the boundaries of innovation and driving our mission forward. As a global medical technology leader for nearly 100 years, a patient’s mobility is enhanced by a Zimmer Biomet product or technology every 8 seconds. As a Zimmer Biomet team member, you will share in our commitment to providing mobility and renewed life to people around the world. To support our talent team, we focus on development opportunities, robust employee resource groups (ERGs), a flexible working environment, location specific competitive total rewards, wellness incentives and a culture of recognition and performance awards. We are committed to creating an environment where every team member feels included, respected, empowered and recognised. What You Can Expect Position Summary Zimmer Biomet is scaling artificial intelligence across the enterprise, and the Enterprise AI team is responsible for the platforms, tools, and services that make that possible. The AI Operations Analyst keeps that platform running day to day: getting the right people access to the right AI tools, keeping consumption and spend visible and under control, and helping employees actually use what they have been given. This is a hands-on operational role at the centre of a fast-moving programme. You will own the request queues, the reporting, and the onboarding experience for AI tooling used across the business, and you will be expected to automate the repetitive parts of that work rather than simply absorb them. You will work closely with IT, Finance, Procurement, and business stakeholders in every region, and you will report directly to the Director of AI. It is also a deliberate entry point into the engineering and delivery side of Enterprise AI. We are looking for someone who wants to build, not just administer. Work Mode: 2 WFH,3 days WFO Location: Bengaluru How You'll Create Impact Why This Role The AI Operations Analyst is designed as a step into AI engineering and delivery. The work starts with operations, but the person who does it well ends up with something rare: a working knowledge of how AI tooling is actually provisioned, paid for, governed, and adopted at enterprise scale. That is the context engineers on this team need and often lack. We will back that progression deliberately: • Every repetitive task in this role is a candidate for automation, and you are expected to write the code that removes it. Your tooling is reviewed, improved, and used by the wider team, not kept as personal scripts. • You will sit with the Enterprise AI engineering and delivery team, take part in their planning and design discussions, and see how platform decisions are made. • As your skills develop, you will take on scoped delivery work alongside the operational remit, such as integrations, internal tooling, data pipelines, and agent workflows, with mentorship from senior engineers. • If you want a career in AI engineering or delivery and are prepared to earn it by first learning the platform from the inside, this role is built for you. What Makes You Stand Out Key Responsibilities Access and Licensing Operations • Own the intake, triage, and fulfilment of access requests for enterprise AI tooling, including GitHub Copilot, the internal AI portal, and other approved AI services. • Work the AI tooling approval queue in ServiceNow, validating entitlement and business justification, escalating exceptions, and meeting agreed service levels. • Provision and maintain user access through Microsoft Entra ID security groups and vendor administration consoles, keeping membership accurate as people join, move, and leave. • Run the joiner, mover, and leaver process for AI tooling, including timely deprovisioning and the reclamation of unused or dormant licences. • Maintain accurate records of licence inventory, assignment, and entitlement, and reconcile them against vendor and procurement data on a regular cycle. • Maintain the operational runbooks and knowledge articles for these processes so the work is repeatable and auditable, and support internal audit and information security requests for access evidence. Cost and Consumption Analytics • Produce recurring reporting on AI platform consumption and spend, drawing on Azure billing and cost management data as the source of record. • Monitor per-user and per-team AI usage budgets, identify users approaching or exceeding their limits, and action or escalate top-up requests according to policy. • Build and maintain dashboards that give the Director of AI and business stakeholders a clear view of consumption, cost per user, and cost per use case. • Deliver showback reporting to business units so each function understands what its AI usage costs and where that cost is going. • Investigate cost anomalies and unexpected consumption spikes, determine the root cause, and recommend corrective action. • Support budget planning and forecasting for AI platform spend, including the licence and consumption inputs to the annual cycle. Adoption and Enablement • Track and report adoption metrics covering activation, active usage, retention, and depth of use across AI tools and business units, and surface where adoption is lagging. • Own the onboarding experience for new AI tool users, including welcome communications, getting-started guidance, and first-week check-ins. • Create and maintain enablement material such as quick-start guides, FAQs, and short how-to content, and keep it current as tooling changes. • Run office hours and support channels for AI tooling questions, and route recurring themes back into documentation and training. • Support the network of AI champions across the business, supplying them with data, materials, and updates. • Feed adoption and support insights back to the Enterprise AI team so that platform, licensing, and training decisions are informed by real usage. Continuous Improvement • Automate repetitive operational work using scripting and pla