Fullstack Software Engineer

Our client in the ICT Sector is currently sourcing Software Engineers to work in Johannesburg to start working as soon as possible.

Longterm Contract: - (initially 6 months, extentable)

Send your CV to [email protected]

70% AI-enabled software delivery | 20% Skills and instruction improvement | 10% architecture and code assurance

Full stack, end-to-end product engineering across frontend, backend, APIs, cloud and data

Digital banking preferred; strong enterprise engineering experience essential

AI-Accelerated Engineering

• Deliver enterprise-grade software using AI-assisted and agentic engineering practices.
• Use the client's enterprise AI platform alongside tools such as GitHub Copilot and Claude to accelerate implementation.
• Direct AI development agents using complete product inputs such as user stories, Figma designs, business rules, design-system components and engineering standards.
• Refine AI Skills, markdown instruction files, prompts, workflows and engineering guardrails to improve quality, consistency and delivery velocity.
• Build reusable AI-enabled engineering capabilities that reduce repetitive work and improve future delivery cycles.
• Evaluate AI-generated outputs critically rather than accepting them at face value.

Full Stack, End-to-End Delivery

• Design, build and maintain modern frontend experiences, mobile applications, backend services, APIs, integration services, cloud-native components and persistence layers.
• Move between frontend, backend and platform concerns according to delivery priorities.
• Work across frameworks and languages rather than being constrained by a single technology ecosystem.
• Use established design-system components and engineering patterns to deliver consistent, high-quality experiences.

Architecture & Engineering 

• Contribute to technical decisions within AI-assisted delivery, with support from more senior engineers where needed.
• Review architecture and implementation choices proposed by AI agents and flag issues promptly.
• Ensure solutions are scalable, maintainable, secure, observable and performant.
• Review AI-generated code critically and apply the same standards as for human-written software.
• Spot emerging technical debt, architectural drift and quality risks, and raise them early.
• Share knowledge and good practices with peers to raise team standards.

Own the engineering quality of AI-generated solutions, including:

• Security and secure coding
• Performance and optimisation
• Reliability and resilience
• Maintainability and code quality
• Accessibility
• Observability
• Automated testing and testability
• Scalability
• CI/CD and DevSecOps
• Technical debt management

Continuous Improvement of the Agentic Engineering System

• Use code review and delivery feedback to improve Skills and instruction files with every iteration.
• Translate engineering standards, coding conventions and security requirements into reusable agent guidance.
• Identify where AI is effective, where human intervention is needed and where workflows can be refined.
• Contribute to establishing operating practices that scale Agentic Engineering across the programme.
• Help make this way of working the emerging standard for software engineers.

Senior Software Engineer (4-8 years experience)

• Proven experience contributing to the design and delivery of complex, enterprise-grade software products.
• Good full stack engineering capability across frontend, backend, APIs, cloud services and data.
• Solid understanding of distributed systems, API-driven architectures and modern application architecture.
• Experience working effectively in complex environments with evolving requirements and technology choices.
• Ability to reason from engineering principles rather than relying exclusively on framework-specific knowledge.
• Commercial experience with modern cross-platform mobile engineering.
• Experience with React Native and/or Flutter is strongly preferred.
• Experience with .NET MAUI, Swift, Kotlin or Ionic is advantageous.
• Demonstrated ability to learn unfamiliar frameworks quickly and make sound implementation decisions within them.
• Hands-on experience using AI-assisted software development tools such as GitHub Copilot, Claude or equivalent enterprise platforms.
• Experience using AI agents to perform software engineering tasks..
• Exposure to creating or refining prompts, markdown instruction files or AI-assisted engineering workflows.
• Developing understanding of how context, instructions, examples and feedback loops influence agent quality.
• Ability to spot obvious AI failure modes such as incorrect assumptions, insecure implementations or superficially plausible but wrong code.

• Software architecture
• Secure software development
• SOLID principles
• Performance engineering
• Design patterns
• Automated testing / TDD
• Domain-driven design
• CI/CD
• API design
• DevSecOps
• Distributed systems
• Observability
• Cloud-native engineering
• Accessibility
• Code quality
• Technical debt management