Senior Software Engineer

Do you use AI agents to actually engineer software, and knows how to control, validate and improve their output? - Then we are looking for you!

Location: Johannesburg

Work Arrangement: On-site

Employment Type: 6 months contract (extendable)

Level: Senior (20 years+)

Salary: Market Related

1. AI / Agentic Software Engineering

• Use AI tools such as GitHub Copilot, Claude or equivalent enterprise AI platforms
• Direct AI agents to perform software engineering tasks
• Create and improve prompts, AI Skills, instruction files and workflows
• Evaluate AI-generated code rather than blindly accepting it
• Build reusable AI-enabled engineering capabilities.

2. Full-Stack Development

Must be comfortable working across:

• Frontend
• Backend
• APIs
• Mobile
• Cloud
• Data
• Integration services
• Persistence/database layers

The candidate must be framework-agnostic rather than tied to one technology.

3. Architecture & Technical Leadership

You will:

• Make and validate architecture decisions
• Review AI-generated designs and code
• Ensure systems are scalable, secure, maintainable and performant
• Identify technical debt and architectural risks
• Coach other engineers
• Raise the overall technical standard.

4. Engineering Quality: Strong knowledge of

Security | Performance | Reliability | Maintainability | Accessibility | Observability | Automated Testing | Scalability | CI/CD | DevSecOps

Must have Technical Background in: Software Engineering

Look for someone with:

• Principal-level software engineering capability
• Complex enterprise software experience
• Strong full-stack experience
• Distributed systems
• API-driven architectures
• Modern application architecture
• Cloud
• Data
• Ability to work across changing technologies.

Mobile / Cross-Platform

Strongly preferred:

• React Native
• Flutter

Advantageous:

• .NET MAUI
• Swift
• Kotlin
• Ionic.

Hands-on experience with:

• GitHub Copilot
• Claude
• Enterprise AI development platforms
• AI-assisted software development
• Directing AI agents to perform software engineering tasks
• Creating/refining AI Skills
• Prompt libraries
• Markdown instruction files
• Coding agents
• Reusable AI engineering workflows
• Understanding how instructions, context, examples and feedback affect AI-agent performance
• Identifying AI failure modes.

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