AI Champion, Centre of Excellence Lead at Lesaka Technologies

The Role

• You will identify, validate, govern and realise the value of AI across the Merchant Division. You will translate business problems into AI powered solutions that improve merchant experiences, reduce cost to serve, enhance operational efficiency and build sustainable competitive advantage.
• You will be the bridge between business ambition and technical AI capability, progressing use cases from the innovation sandbox through to production.

What You'll Own

Use Case Pipeline

• Build use cases with stakeholders across Sales, Operations, Finance, Product and Marketing. Assess each against business value, feasibility and risk.
• Maintain a prioritised AI use case pipeline aligned to CIO and COO objectives.
• Design and run the Innovation Sandbox as a structured environment for validating and de risking use cases before production investment.
• Define graduation criteria from sandbox to production. Provide regular pipeline and value visibility to the CIO and COO.

Sandbox to Production Delivery

• Lead end to end delivery of AI use cases from validated prototype to production. Partner with DevOps, Architecture, Infrastructure and application teams.
• Define and maintain the AI delivery framework covering model development, integration, testing, deployment, monitoring and ongoing performance management.
• Integrate AI solutions into Salesforce CRM, ERP, Core Platform and DevOps pipelines with minimal disruption.
• Establish post deployment monitoring for accuracy, drift, business impact and cost.
• Build a reusable library of AI components, prompts, models and integration patterns.

Governance, Ethics and Risk

• Develop and maintain the Lesaka AI governance framework covering acceptable use, data ethics, bias assessment, explainability, model risk and regulatory compliance.
• Conduct risk assessments for every use case before sandbox entry and again before production graduation.
• Ensure AI solutions comply with risk, fraud, compliance, data protection and financial services regulatory expectations.
• Maintain the AI risk register. Stay current with evolving AI regulation and brief the CIO proactively.

Literacy and Capability

• Design and deliver an AI literacy programme for IT and business stakeholders.
• Build AI fluency within IT by embedding AI aware engineering and prompt engineering practices across delivery teams.
• Act as the internal AI thought leader. Communicate the roadmap, showcase wins and build organisational appetite.
• Partner with Human Capital on AI skills assessments and targeted upskilling.

What You'll Bring

You have already taken AI from concept to production at least once and you can talk credibly about what worked and what you would do differently. You hold the line on responsible AI without being precious about it.

• Hands on experience designing, building or deploying AI and ML solutions including at least one production deployment.
• Working knowledge of LLMs (Anthropic, OpenAI, Google), ML platforms (SageMaker, Azure ML, Vertex AI) and Python ML frameworks.
• Familiarity with vector databases, RAG architectures, MLOps toolchains and feature stores.
• Experience with model risk assessment, AI ethics frameworks and POPIA compliance.
• Strong stakeholder engagement and business case development skills.

How You'll Show Up

• Result orientated. Outcomes over activity every time.
• Customer focus. Every use case justifies itself in merchant or staff impact.
• Entrepreneurship and innovating. You spot opportunities others miss and pursue them with discipline.
• Organisational sensitivity. You build coalitions rather than just technology.
• Analysing and forming opinions. You separate hype from genuine signal.

Experience & Qualifications

Experience

• 1 to 5 years in technology, data or analytics with at least 1 year of hands on AI or ML solution work.
• Demonstrated track record of taking AI from concept through to production.
• Experience in a complex multi stakeholder business environment.
• Financial services, fintech or payments sector exposure advantageous.

Qualifications & Certifications

• Honours degree in Computer Science, Data Science, AI, Information Systems, Engineering or Mathematics. Master's in AI, ML or Data Science advantageous.
• AWS Machine Learning Specialty, Google Professional ML Engineer or Microsoft Azure AI Engineer certification (advantageous).
• Recognised AI ethics or responsible AI training (advantageous).
• Prompt engineering or generative AI practitioner certification (advantageous).

Closing Date 15 May 2026