Enter a job title or keyword
AI Engineer (Senior)
Job Location:
Job Location:
Pretoria - South Africa
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
19 August 2026 (17 days ago)
Posted:
Application Deadline:
22 November 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Reference: JHB001593-NS-1
ESSENTIAL SKILLS:
ADVANTAGEOUS SKILLS:
ESSENTIAL SKILLS:
- Strong experience with AWS services for data engineering including S3 Lambda VPC IAM and CloudWatch.
- Proven proficiency in Python (Python 3.x) and PySpark for building ETL and data-processing pipelines.2
- Hands-on experience with data-store technologies relevant for data engineers such as DynamoDB or other
- NoSQL and relational databases.
- Solid understanding of data engineering concepts: ETL/ELT data modelling schema design and analytical
- processing.
- Experience building and maintaining CI/CD pipelines and automated testing (GitHub Actions or similar) for data
- and ML workflows.
- Proven use of Infrastructure as Code (Terraform/Terragrunt) to provision and manage cloud infrastructure.
- Knowledge of containerisation and orchestration patterns (ECS Step Functions or similar) for production data
- workloads.
- Strong skills in monitoring logging and alerting for data pipelines and ML platform components (CloudWatch
- metrics logs).
- Practical experience integrating data workflows with MLOps pipelines and model lifecycle tooling (SageMaker
- SageMaker Pipelines or equivalent).
- Strong problem solving analytical skills and ability to communicate technical concepts to both technical and non-technical stakeholders.
ADVANTAGEOUS SKILLS:
- Experience with AI engineering workflows including model serving feature stores and model observability.
- Understanding of agentic systems and multi-agent architectures relevant to Agent Fabric-style platforms.
- Familiarity with Amazon Athena AWS Glue and streaming technologies (Kinesis Kafka) for real-time/near-realtime
- pipelines.
- Experience with feature engineering at scale and data preparation for ML teams.
- Familiarity with Databricks or managed Spark environments and optimisation of Spark jobs.
- Exposure to low-code/no-code tooling that assists business teams in data access and insights.
- Familiarity with data modelling and SQL tuning for analytical workloads (Oracle SQL or equivalent).
- Knowledge of security hardening and networking best practices in AWS for data platforms.
- Experience mentoring junior engineers and leading cross-functional data integration efforts.
- Familiarity with monitoring model behaviour and evaluating LLM outputs as part of quality assurance
Duties & Responsibilities
ROLE & RESPONSIBILITIES:
QUALIFICATIONS/EXPERIENCE:
- Design build and operate scalable secure data pipelines to support MLOps and Agent Fabric workloads.
- Integrate diverse data sources and ensure robust data ingestion transformation and availability for ML teams.
- Collaborate with ML Engineers and AI teams to productionise models and embed data requirements into
- MLOps pipelines.
- Implement Infrastructure as Code (Terraform/Terragrunt) to provision and manage platform components.
- Build and maintain CI/CD pipelines and automated testing for data and ML deliveries.
- Ensure operational excellence through monitoring alerting and logging of data workflows and models.
- Participate in data modelling schema design and optimisation for efficient feature storage and retrieval.
- Improve data security and networking posture across the data platform in collaboration with DevOps and
- security teams.
- Enable business users and analysts by supporting data access patterns low-code solutions and documentation.
- Mentor and coach junior data engineers sharing best practices in data engineering and MLOps.
- Work in an Agile delivery model contributing to planning estimation and delivery of features.
- Evaluate and recommend tools and patterns for supporting agentic systems and AI-driven integrations within the Agent Fabric.
QUALIFICATIONS/EXPERIENCE:
- Degree in Data Science Computer Science Statistics Engineering or equivalent relevant experience
- Minimum of 3-5 years experience in data science AI applications or related fields with demonstrated
- stakeholder management experience
- Proven track record of designing or enabling AI/ML/Data Engineering solutions and working with cross functional delivery teams to deploy them into production.
Required Experience:
Senior IC
