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Ozow is a leading fintech company redefining digital payments in South Africa and beyond. We are seeking a Senior Software Engineer (AI-Enabled) to join our development team and lead the design and delivery of solutions powering our digital payment platforms.
This is a senior, hands-on engineering role focused on building and modernizing software with AI integrated throughout the development lifecycle—not designing autonomous agent workflows.
Key Responsibilities:
Software Development: Lead the design and delivery of software solutions with cross-functional teams, translating business problems into technical approaches that meet high-quality standards.
AI-Enabled Replatforming: Lead the replatforming of existing systems onto modern, AI-native services, defining migration approach, sequencing, and risk controls to keep current platforms live, stable, and secure.
AI Feature Development: Design and build features that integrate with large language models (LLMs) beyond simple request-response, including context engineering, embeddings, and retrieval-augmented generation (RAG). Own the data layer behind AI features, including embeddings and vector search, alongside relational and NoSQL data stores.
Coding: Write clean, efficient, and maintainable code that sets the example for the team, using AI coding tools to move faster without lowering the bar on quality, security, or testing.
Responsible AI Delivery: Define and maintain the team's standards and guardrails for using AI safely across the software development lifecycle. Ensure AI-generated output is validated, account for the non-deterministic nature of AI models, and protect sensitive and payment data when working with AI tools.
Technical Problem Solving: Diagnose and resolve complex technical issues, including production incidents, and implement fixes that prevent recurrence.
System Architecture: Own the design and architecture of systems you work on, including how AI components fit into them. Make and document trade-offs across scalability, security, performance, and cost. Ensure services handle high-volume payment traffic and identify and resolve performance bottlenecks.
Code Reviews: Lead code reviews, including AI-assisted code, setting the bar for code quality and sharing knowledge across the team.
Testing and Quality: Define the testing approach for your area, including unit and integration tests and test-driven development where it adds value. Establish how the team tests and monitors AI features with non-deterministic outputs for reliable production behavior.
DevOps and Deployment: Own your services through to production—containerize services, improve CI/CD pipelines, and deploy to cloud environments (AWS or Azure). Apply and champion DevOps principles, owning the reliability and monitoring of what the team ships.
Agile Development: Work in an Agile environment, contributing to sprint planning, estimation, prioritization, and helping the team improve how it delivers.
Documentation: Create and maintain technical documentation, including architecture decisions and standards for using AI in development.
Technical Leadership and Mentoring: Mentor and coach engineers in effective and disciplined use of AI tools. Champion AI-enabled ways of working across engineering, sharing what works and helping colleagues make the shift.
Requirements:
- At least 7+ years of experience as a Software Engineer or Software Developer, including leading technical delivery, ideally with an IT Diploma or Degree
- Strong development skills in .NET 8 C#, JavaScript and ReactJs, with Python strongly beneficial (polyglots preferred)
- Proven experience developing against LLMs beyond basic prompt and response, such as context engineering, embeddings, and retrieval-augmented generation (RAG)
- Track record of shipping AI-powered features to production, not only prototypes
- Experience leading a migration or replatforming of a live, high-volume system
- Strong system design and architecture experience, including relational, NoSQL, and vector databases
- Experience with cloud services (AWS or Azure) and containerization (Docker, Kubernetes)
- Ability to influence and coach others, with a curious, pragmatic attitude towards AI as the expected way of working
