Job Description

Overview:
Develop and manage scalable AI infrastructure strategies for cloud and on-prem environments to support enterprise AI workloads.
Key Responsibilities:

• Architect infrastructure for AI training, inferencing, and deployment.
• Design cost-efficient, secure, high-performance AI environments.
• Implement MLOps pipelines and Infrastructure as Code (IaC).
• Manage orchestration using Kubernetes and real-time monitoring.
• Ensure seamless integration with enterprise IT systems.
• Drive governance, compliance, and performance tuning.

Experience & Skills:

• 8+ years in AI infrastructure/cloud computing.
• Hands-on with Terraform, Ansible, Kubernetes, Docker.
• Deep experience with cloud platforms (AWS, Azure, GCP).
• Proven performance and cost optimization strategies for AI systems.

CVS to be sent directly to:
Platform Architect:
Education:

• Bachelor's degree in Computer Science, Data Science, Information Technology or a related field
• Relevant certifications in data engineering or AI/cloud platforms (preferred)

Experience:

• 8+ years of experience in AI platform architecture, deployment, and optimization, ideally within large-scale telecom environments
• Strong background in designing enterprise-scale AI platforms integrating with IT and cloud environments
• Hands on experience in AI platform development, API management, or MLOps practice
• Experience of working in a dynamic, fast-paced environment

Skills :

• Proficiency in AI and machine learning frameworks (TensorFlow, PyTorch, Keras)
• Proficient with public cloud platforms (AWS, Azure, Google Cloud) for AI and telecom solutions
• Experience in containerization and orchestration tools (e.g. : Docker, Kubernetes) for AI deployment
• Strong understanding of telecom networks (5G, IoT, edge computing) and how AI can optimize them
• In-depth Knowledge of security protocols in AI and telecom, including data privacy, encryption, and secure access management