R 900 000 - R 1 300 000 Annually (Negotiable)
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.
- 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.
Education
Platform Architect:
- Bachelors degree in Computer Science, Data Science, Information Technology or a related field
- Relevant certifications in data engineering or AI/cloud platforms (preferred)
- 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
- 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
Lufuno Ramarumo
