Key Responsibilities :

- Own the setup, configuration, and maintenance of VMs, containers, GPU clusters, and cloud-native environments across DEV and PROD ecosystems.

- Design and implement cloud-native platforms for AI/ML and data-driven solutions.

- Define and drive cloud migration strategies across Azure and AWS environments.

- Assess application cloud readiness and analyze dependencies across applications, databases, and middleware.

- Provision Landing Zones, cloud infrastructure, and platform services using Infrastructure as Code (IaC).

- Deploy applications using serverless and cloud-native services.

- Build and automate DevOps, DataOps, and MLOps pipelines to enable continuous integration and continuous deployment (CI/CD).

- Provision GPU clusters and ML container environments for foundation model deployment, fine-tuning, and model optimization.

- Develop cloud service catalogs, reusable cloud blueprints, and automated ML/data workflows.

- Monitor, govern, and optimize cloud consumption using FinOps best practices.

- Ensure security, scalability, reliability, and operational excellence across cloud platforms.

Required Skills & Qualifications :

Cloud & Infrastructure :

- Strong understanding of cloud architecture concepts including : Virtual Machines, Serverless Computing, Private/Public/Hybrid Cloud, API Gateway, Auto Scaling, Cloud Migration, CDN, Event-Driven Architecture, DNS, Microservices, Middleware, VPC, and Storage Services.

Networking and Security :

- Cloud Security experience with IAM, RBAC, MFA, Data Encryption, Container Security, IPS/HIPS, Virtual Firewalls, and Anti-malware solutions.

Storage & Data :

- Knowledge of Block, Object, and Archive Storage, and cost/performance optimization techniques.

Cloud Platforms :

- Expert-level hands-on experience with Azure or AWS infrastructure, platform, and application services.

- Experience designing and deploying large-scale enterprise cloud-native solutions.

AI/ML & Data Platforms :

- Experience supporting AI/ML workloads on cloud platforms.

- Exposure to GPU infrastructure, MLOps, and DataOps frameworks.

- Understanding of cloud-native AI/ML services and data processing platforms.

Migration & Automation :

- Proven experience executing application migration and modernization initiatives, including lift-and-shift migrations.

- Strong automation and Infrastructure-as-Code expertise.

Preferred Skills :

- Data Engineering, DataOps, MLOps, Generative AI / AI-ML platforms, Kubernetes and Container Orchestration, Terraform, Bicep, or CloudFormation.