Senior Data Scientist; AI & Agentic Systems

Senior Data Scientist (AI & Agentic Systems)

Pretoria, South Africa | Posted on 13/07/2026

Are you passionate about Artificial Intelligence, Generative AI, and building intelligent systems that solve real business problems?

We're looking for a Senior Data Scientist who thrives on designing enterprise-scale AI solutions, building autonomous AI agents, and creating intelligent platforms that deliver meaningful impact. This is an opportunity to work on cutting‑edge AI technologies with a global team while helping shape the future of enterprise AI.

If you're someone who enjoys solving complex technical challenges, leading architectural decisions, and turning innovative ideas into production‑ready solutions, this could be the perfect role for you.

• Designing and building agentic AI system architectures using Amazon Bedrock Agent Core and modern agent frameworks
• Creating intelligent multi-step reasoning workflows with tool integration and orchestration
• Defining AI model strategies, including architecture selection, fine‑tuning, inference, and performance optimisation
• Designing scalable and resilient AI deployments using Docker and Kubernetes
• Building secure, low‑latency networking architectures for AI workloads
• Conducting systems performance engineering, including hardware selection, load testing, stress testing, and capacity planning
• Establishing MLOps and GenAI Ops practices, including CI/CD pipelines, model versioning, and deployment automation
• Implementing monitoring, logging, observability, and incident response for production AI environments
• Building enterprise Retrieval‑Augmented Generation (RAG) solutions and intelligent AI workflows
• Providing technical leadership, mentoring engineers, and influencing architecture and engineering best practices

• Amazon Bedrock Agent Core
• Agent frameworks such as Lang Chain, Lang Graph, or Strands Agents
• Designing agentic AI architectures
• Multi‑agent orchestration and workflow automation
• Py Torch
• Tensor Flow
• Python
• Docker
• Retrieval‑Augmented Generation (RAG)
• MLOps and GenAI Ops
• CI/CD for Machine Learning
• Model versioning and deployment automation
• AI observability and monitoring
• Networking for machine learning workloads
• Systems performance engineering

• Amazon Bedrock
• Terraform or Terragrunt
• AWS Lambda
• Step Functions
• Event Bridge
• Cloud security and IAM best practices
• Data Engineering and ETL pipelines
• Grafana
• Cloud Watch
• Hybrid or multi‑cloud AI deployments
• Model optimisation techniques such as batching, quantisation, and distillation
• Enterprise environments operating within regulated industries

• A degree in Computer Science, Engineering, Statistics, or a related field
• A proven track record of delivering enterprise‑scale AI solutions
• Experience owning AI architecture from design through to production
• Strong stakeholder management and technical leadership experience
• Cutting‑edge global IT system landscape and processes
• Flexible working of 1960 hours in a 12‑month period
• High Work‑Life balance
• Remote / On‑site work location flexibility
• Highly motivating, energetic, and fast‑paced working environment
• Modern, state‑of‑the‑art offices
• Dynamic Global Team collaboration
• Application of the Agile Working Model Methodology