At VIATRIS, we see healthcare not as it is but as it should be. We act courageously and are uniquely positioned to be a source of stability in a world of evolving healthcare needs.

Viatris empowers people worldwide to live healthier at every stage of life.

We do so via

- Access – Providing high quality trusted medicines regardless of geography or circumstance;
- Leadership – Advancing sustainable operations and cutting-edge solutions to improve patient health; and
- Partnership – Leveraging our collective expertise to connect people to products and services.

Every day, we rise to the challenge to make a difference and here’s how the AI/ML Platform Engineer– Manufacturing Analytics role, will make an impact:

Role Purpose

Viatris is building an enterprise AI capability based on operations domain that can scale safely and deliver real operational value. The AI/ML Platform Engineer will help build and operate the technical foundation required to move AI/ML capabilities from project-based implementations into governed, observable, production-grade enterprise capabilities.

This is a hands-on platform engineering role focused on the systems, patterns, environments, controls, and automation required for production AI/ML delivery.

This role will not focus on building one-off AI use cases. It is focused on making AI/ML engineering repeatable, reliable, secure, and scalable across the enterprise.

Key Responsibilities

- As an AI/ML Platform Engineer, you will be at the heart of building, operating, and evolving the cloud-native AI/ML platform that powers data, analytics, artificial intelligence, and agentic capabilities across the organization.
- You will own critical platform components end-to-end — from containerized workloads, streaming pipelines, networking, security, and CI/CD automation, through ML/API gateway and multi-provider model integration, to Model Context Protocol (MCP) tooling and Agent-to-Agent (A2A) communication patterns.
- You will solve complex, operationally important engineering challenges by filtering and prioritizing inputs from a wide range of internal and external sources,



drawing on an in-depth understanding of how platform sub-functions work together.
- Acting as a key technical liaison across Cloud, Cybersecurity, Governance, and adjacent engineering teams, you will ensure the platform remains aligned with enterprise standards and emerging best practices. Your decisions will be guided by resource availability and organizational objectives, and you will contribute to defining team responsibilities, engineering standards, and platform governance practices that raise the quality bar across closely related teams.
- You will work closely with AI/ML engineers and Data scientists to develop, deploy, and monitor machine-learning models and AI services at production scale, working with a pragmatic, reliability-first mindset that directly shapes the technical direction of a platform driving meaningful business outcomes.

Educational Qualification

- 5 or more years of relevant industry experience in software, cloud, or platform engineering, including large language model operations (MLOps) in a production environment.
- Degree in Computer Science, Software Engineering, or a related field, or equivalent professional experience.

Experience Required

- AI/ML, MLOps & Agentic Platforms

1. Hands-on experience with ML/API gateway technologies such as LiteLLM or comparable solutions, and multi-provider integration across major cloud AI platforms including Azure OpenAI, Azure AI Foundry.
2. Experience deploying, scaling, and monitoring AI/ML workloads and model-serving APIs, collaborating effectively with AI/ML engineers and data scientists to bring models into production.
3. Practical experience with MCP (Model Context Protocol) concepts — tools, resources, prompts, and server lifecycle management — and familiarity with Agent-to-Agent (A2A) communication patterns such as agent discovery and task delegation.
4.



Comfortable working with agentic AI frameworks (such as LangGraph, LlamaIndex or comparable technologies) to support the deployment and operation of agent workloads.
5. Familiarity with observability and monitoring tools used in AI/ML environments, such as CloudWatch, Prometheus, Grafana, or LLM-specific evaluation tooling.

- Engineering & Automation

1. Proficiency developing production-grade backend services in Python using asynchronous programming frameworks; experience with Rust would be advantageous.
2. Experience building and maintaining CI/CD pipelines and infrastructure automation — containerisation with Docker, pipeline automation with Azure DevOps or similar tooling — with disciplined version-control practices in collaborative environments.
3. Ability to perform performance testing and troubleshooting for APIs and platform services, with a focus on scalability and reliability engineering.
4. Exposure to agent memory or state management, Envoy Proxy, mTLS, or API security hardening.
5. Databricks platform engineering experience, including workspaces, clusters/serverless, Unity Catalog, MLflow, model serving, jobs/workflows, permissions, and cost controls.

- Security & Identity

1. Experience with identity and access management technologies including Entra ID, JWT, OIDC, SSO, OAuth 2.0, LDAP, API keys, and related IAM methods.
2. Confident implementing platform security — Transport Layer Security, secrets management, access controls, and standard authentication flows.
3. Working knowledge of API security practices applied within established guidelines.

- Leadership & Ways of Working

1. Demonstrated ability to lead junior team members, set team priorities, and drive platform quality — balancing hands-on technical depth with team accountability and a focus on scalable, well-governed engineering.
2. A collaborative team player who communicates clearly, follows established processes, and is comfortable seeking guidance when navigating new or complex challenges.
3. Experience of working as part of Global team involving multiple stakeholders, contract partners

📌 AI/ML Platform Engineer- Manufacturing Analytics (Hyderabad)
🏢 Viatris
📍 Hyderabad