Description
Application Development
Design, build, and maintain features, integrations, and defect fixes across the Group's AI applications.
Deliver changes through the team's standard development and review workflow.
Implement changes to a standard that passes senior code review.
Contribute to technical design discussions for new and existing AI applications.
Use AI development tools to work efficiently, while remaining accountable for the quality of the output.
Testing and Quality
Establish and maintain automated testing for AI applications.
Integrate automated test execution into the release process so that changes are verified before reaching production.
Establish evaluation and regression testing for AI behaviour, covering prompts, model outputs, and agent workflows.
Validate model, prompt, and provider changes before release.
Maintain test cases and test data, and verify defect fixes and releases before they reach users.
Report test results and quality risks, and raise concerns where the evidence does not support release.
Application Support
Provide second-line application support, triaging reported issues and establishing their impact.
Reproduce and diagnose defects, resolving them in code where possible.
Escalate complex or high-impact problems with clear technical detail.
Agree service levels and incident severity definitions with each application's business owner, and establish the means to report against them.
Track recurring issues and feed them into the product backlog.
Provide practical guidance to users of AI applications.
Monitoring, Documentation and Continuous Improvement
Monitor the health, reliability, and output quality of AI applications.
Translate what monitoring shows into prioritised fixes and improvements.
Maintain technical documentation for supported applications.
Contribute to improving the team's development, testing, and release practices. • Apply data privacy and security obligations when working with AI applications and the data they process.
Requirements
Matric / Grade 12 — Required
Degree or National Diploma in Computer Science, Information Technology, Software Engineering, Infrastructure Engineering, or related technical field — Advantageous
Professional Certifications
Microsoft, Google, AWS, or AI productivity platform certifications — Advantageous
Technical support, knowledge management, instructional design, or learning facilitation certifications — Advantageous
Experience
2-4 years' experience in software development, application support, or software testing - Required
Hands-on experience building or maintaining web applications (for example TypeScript, React or Next.js, and SQL databases) - Required
Structured software testing experience, including test design and automated testing - Required
Working knowledge of Git-based development workflows, including branching, pull requests, and code review - Required
Experience with continuous integration pipelines - Advantageous
Exposure to AI tools, LLM platforms, or AI-enabled applications - Advantageous
Experience maintaining technical documentation or operational support resources - Advantageous
Experience troubleshooting user issues in an operational environment - Advantageous
Skills & Capabilities
Software development. Able to implement features and defect fixes in a modern web application stack to a standard that passes senior code review.
Software testing. Able to design test cases and build automated tests for web applications.
AI evaluation testing. Able to build tests for prompts, model outputs, and agent behaviour, and to interpret the results.
Troubleshooting. Able to reproduce a reported defect from incomplete information, isolate the cause, and either resolve it or escalate with clear technical detail.
AI-assisted development. Able to use AI development tools effectively while retaining judgement over the quality of the output.
Technical communication. Able to explain technical detail clearly to technical and non technical audiences, and to produce usable technical documentation.
Stakeholder engagement. Able to work productively with users of AI applications and with senior engineers, and to manage expectations on resolution and delivery.
Adaptability and learning agility in a fast-evolving AI and technology environment.