AI Operations Analyst
Zimmer Biomet · Bangalore, Karnataka ·
- Category
- Operations
Zimmer Biomet · Bangalore, Karnataka ·
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.
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
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:
Key Responsibilities
Access and Licensing Operations
Cost and Consumption Analytics
Adoption and Enablement
Continuous Improvement
Qualifications
Education
Required Experience
Required Technical Skills
Attributes
Preferred
EOE/M/F/Vet/Disability