AI & Data Solutions Architect

Sabenza IT & Recruitment; Johannesburg; On-site; ZAR 900 000 - 1 200 000; Full time

Job summary

A leading IT recruitment firm is seeking a Senior AI & Data Solutions Architect to design enterprise-scale AI solutions in Johannesburg. The role requires proficiency in AI/ML concepts and platforms like Azure, AWS, and GCP. Ideal candidates will have hands-on experience with Generative AI and LLM-based applications, alongside skills in MLOps. You will influence AI architecture and collaborate with senior leaders, driving significant transformation initiatives within enterprise settings.

Qualifications

• Strong understanding of AI/ML concepts and architectures.
• Advanced proficiency in Python is required.
• Hands-on experience with GenAI and LLM-based applications.

Responsibilities

• Architect and deliver end-to-end AI and GenAI solutions.
• Design scalable AI and data platforms across Azure, AWS, and/or GCP.
• Develop, train, deploy, and operate AI/ML models using MLOps practices.

Skills

AI/ML concepts and solution architectures

Python

GenAI, LLM-based applications

MLOps pipelines

NVIDIA H200 / GPU-based workloads

Cloud-based data storage

Tools

Azure

AWS

GCP

Kubernetes

Docker

Job description

Build the future of AI at enterprise scale

Are you passionate about Generative AI, large-scale data platforms, and cloud-native architecture? Do you want to design AI solutions that move beyond experimentation and into real-world, business-critical impact?

We are looking for a senior AI & Data Solutions Architect to lead the design and delivery of next-generation AI, GenAI, and data-driven platforms within a complex enterprise environment. This role sits at the intersection of AI innovation, cloud architecture, and business transformation, with exposure to telecom environments and cutting-edge GPU-powered AI workloads.

Requirements

What You’ll Be Doing

• Architect and deliver end-to-end AI and GenAI solutions aligned to strategic business objectives
• Design scalable AI and data platforms across Azure, AWS, and/or GCP
• Build and refine LLM-based applications, including advanced prompt engineering
• Develop, train, deploy, and operate AI/ML models using modern MLOps practices
• Integrate AI solutions with cloud-native AI services, LLM platforms, and enterprise systems
• Leverage platforms such as Azure Machine Learning for model lifecycle management
• Design and support GPU-powered AI workloads, including NVIDIA H-series architectures
• Ensure ethical, responsible, and compliant AI across all implementations
• Stay ahead of the curve on Generative AI, LLMs, and AI infrastructure trends
• Collaborate closely with business leaders, data engineers, IT teams, and external partners

What We’re Looking For

Must-Have Skills & Experience

• Strong understanding of AI/ML concepts and solution architectures
• Advanced Python proficiency
• Hands‑on experience with GenAI, LLM‑based applications, and prompt engineering
• Solid understanding of MLOps pipelines and model lifecycle management
• Exposure to NVIDIA H200 / GPU‑based AI workloads
• Experience working within or alongside telecom environments
• Deep, hands‑on experience with Azure, AWS, and/or GCP
• Strong knowledge of cloud‑based data storage and processing platforms

Nice-to-Have (Bonus)

• Kubernetes and Docker
• Azure DevOps
• Azure Cosmos DB
• Java and/or Ruby on Rails
• Experience managing large‑scale, GPU‑intensive AI platforms

Screening Questions

Describe your experience designing and deploying GenAI or LLM‑based solutions.

What is your hands‑on experience with MLOps pipelines in a cloud environment?

Which cloud platforms (Azure/AWS/GCP) have you architected AI solutions on, and at what scale?

Have you worked with GPU‑based AI workloads (e.g., NVIDIA H‑series)? Please explain.

What exposure do you have to telecom data or systems, if any?

Benefits

Why Join?

• Architect enterprise‑scale AI solutions, not just proofs of concept
• Work with cutting‑edge GenAI and GPU technology
• Influence strategy, architecture, and standards across a large organisation
• Collaborate with senior stakeholders on high‑impact AI transformation initiatives
• Be part of a team shaping the future of AI adoption in telecom and enterprise environments