Cloud Infrastructure Engineer

Zinnov is hiring for the role of Cloud Infrastructure Engineer
on behalf of our Global MNC MedTech client company a company where technology sits at the centre of everything: powering how the core business operates day to day and shaping the products and digital solutions that will define the future of patient care. This role is part of the companys establishment of their new India Global Capability Centre (GCC) in Bengaluru which will drive enterprise technology, digital transformation and innovation for its global operations and contributing to technology that ultimately helps millions of people around the world.

How you'll make an impact

• Design, implement, and support hosting and cloud infrastructure services, including onpremises, hybrid, and public cloud environments, in alignment with enterprise architecture standards
• Operate and maintain cloud and hosting platforms to meet availability, performance, security, and compliance requirements across global environments
• Build and operate AI landing zones and cloudnative AI services on AWS and Azure, ensuring consistent architecture, security, and observability across the Enterprise AI Platform.
• Deploy and manage Kubernetesbased AI workloads and GPU clusters, including containerized inference endpoints, model runtimes, and autoscaling patterns for LLM and traditional ML workloads.
• Automate infrastructure delivery using Terraform, Ansible, ArgoCD, and GitOps practices to accelerate provisioning of AI and general compute environments.
• Support AI inference platforms and enterprise LLM services (Azure OpenAI, Amazon Bedrock/SageMaker) in partnership with the Data & AI team.
• Apply policyascode (OPA) and cost guardrails (Kubecost) to enforce security, compliance, and financial accountability across cloud and AI workloads.
• Partner with application, security, and network teams to deliver infrastructure solutions that support business and technology roadmaps
• Monitor, troubleshoot, and resolve infrastructure incidents and problems, contributing to root cause analysis and longterm remediation
• Support cloud migration and modernization initiatives, including workload onboarding, optimization, and cost management activities
• Contribute to documentation, standards, and operational runbooks to ensure consistent and repeatable service delivery
• Engage with external service providers and vendors to ensure services meet contractual and performance expectations

What you'll bring

Qualifications

Education

• Bachelors degree required in Information Technology, Computer Science, Engineering, or a related discipline
• Advanced degree preferred in a technology or businessrelated field

Experience and Skills

Required

• 4-7 years of experience supporting enterprise hosting, infrastructure, cloud platforms, or hybrid cloud environments in professional IT services environment
• Handson experience with cloudnative infrastructure and AI platform tooling such as: Kubernetes, OpenShift, Terraform, Ansible, ArgoCD, Istio, Harness, Backstage, plus exposure to Kubecost, OPA, and AI Agents. Working knowledge of AWS and/or Azure core services, virtualization, Windows/Linux environments, and observability tools (Prometheus, Grafana, OpenTelemetry).
• Hands-on experience with AWS and/or Azure cloud services, virtualization platforms, Windows/Linux environments, and infrastructure monitoring tools.
• Working knowledge of infrastructure security, identity management, backup, disaster recovery, and compliance controls
• Experience with scripting and automation tools such as PowerShell, Python, Terraform, or Ansible.
• Strong business skills, including the ability to understand service impacts, prioritize work based on business needs, and communicate technical concepts to nontechnical stakeholders
• Demonstrated leadership skills through collaboration, accountability, and ownership of service outcomes, even without direct people management responsibility

Preferred

• Experience with hybrid cloud architectures and cloud migration initiatives in a large, regulated enterprise environment
• Experience deploying GPU clusters, AI landing zones, or hybrid AI platforms in enterprise or regulated environments.
• Familiarity with enterprise LLM platforms and inference services (Azure OpenAI, Amazon Bedrock, SageMaker) and cost/performance optimization of AI workloads.
• Exposure to IT service management practices (incident, problem, change) and continuous improvement methodologies
• Ability to influence peers and stakeholders, demonstrating informal leadership and a customerfocused mindset