AI Engineer

Cape Union Mart Group; Cape Town; Hybrid; ZAR 700,000 - 1,100,000; Full time

Job summary

Cape Union Mart Group is seeking an AI Engineer to join the BI team, delivering AI capabilities across the business in a hybrid role. You will balance hands-on engineering with cross-functional collaboration to translate business problems into scalable AI solutions.

You will engage with stakeholders from Planning, Merchandising, Supply Chain and Finance, delivering production-grade AI that drives measurable value and adoption across units.

Qualifications

• Strong practical experience in AI or machine learning engineering.
• Experience with large language models, retrieval-augmented generation, and agent/orchestration frameworks.
• Proficiency with APIs and systems integration in cloud environments.
• Experience moving AI from PoC to production and integrating with enterprise data platforms.

Responsibilities

• Design, build, deploy, and maintain production-ready AI solutions, including LLM apps, RAG pipelines, agents, and automation.
• Build AI solutions on top of Oracle Analytics Cloud and data warehouse platforms.
• Extend BI with natural language querying, automated insights, anomaly detection, and AI-assisted analysis.
• Ensure AI outputs are grounded in accurate, governed data and integrated into existing data pipelines and BI tools.
• Monitor, maintain, and secure deployed AI solutions to ensure reliability and business relevance.

Skills

AI/ML engineering

Large language models

Retrieval-augmented generation

Agent/orchestration frameworks

APIs and systems integration

Cloud-based AI tooling

Tools

Oracle Analytics Cloud

Data warehouse platform

Job description

About the Role

The AI Engineer will form part of the BI team while delivering AI capability across the wider business.

This is a hybrid role combining hands‑on technical engineering with meaningful cross-functional engagement. The successful candidate will identify, prioritise, design, and deliver AI‑driven solutions that create measurable value across multiple business units.

The role is not limited to the BI team’s existing backlog and is not a purely technical development position. Success will depend equally on strong engineering capability and the ability to work directly with non‑technical stakeholders, understand business challenges, and translate those challenges into practical, scalable solutions.

The AI Engineer will be expected to proactively identify opportunities, establish trusted relationships across the organisation, and help the business adopt AI responsibly and effectively.

Key Responsibilities:

1. AI Engineering and Technical Delivery

• Design, build, deploy, and maintain production‑ready AI solutions, including:
  • Large language model applications
  • Retrieval‑augmented generation pipelines
  • Intelligent agents and workflow automation
  • Predictive and machine learning models
• Build AI solutions on top of the organisation’s Oracle Analytics Cloud and data warehouse platform.
• Extend existing BI and reporting capabilities through:
  • Natural language querying
  • Automated insight generation
  • Anomaly and exception detection
  • AI‑assisted analysis and decision support
• Ensure that AI outputs are grounded in accurate, governed, and trusted business data.
• Integrate AI solutions into existing data pipelines, BI tools, and operational processes.
• Monitor and maintain deployed solutions to ensure reliability, quality, security, and ongoing business relevance.

1. Cross‑Functional Engagement

• Act as a primary point of contact for AI opportunities and use cases across the business.
• Engage directly with stakeholders in areas such as Planning, Merchandising, Supply Chain, Finance, and other business units.
• Facilitate discovery discussions to understand business problems, current processes, data requirements, and desired outcomes.
• Explain AI capabilities, limitations, risks, and outcomes in clear, non‑technical language.
• Partner proactively with business unit leaders to identify quick wins and valuable use cases rather than relying only on incoming requests.

1. AI Strategy, Standards, and Governance

• Contribute to a practical and proportionate AI governance approach.
• Promote the responsible use of AI and ensure that solutions align with organisational data and technology standards.
• Provide concise updates to BI leadership and executive sponsors.
• Contribute to the organisation’s broader AI roadmap by identifying recurring needs, reusable capabilities, and opportunities for scale.

Experience and Capabilities:

Technical Requirements

The successful candidate should have:

• Strong practical experience in AI or machine learning engineering.
• Demonstrated experience working with:
  • Large language models
  • Retrieval‑augmented generation
  • Agent or orchestration frameworks
  • APIs and systems integration
  • Cloud‑based AI tooling
• Experience developing solutions that move beyond proof of concept into reliable business or production use.
• Experience working with enterprise data platforms and data warehouses.
• A strong understanding of data quality, governance, security, testing, and monitoring as they relate to AI solutions.

Business Engagement Requirements

The successful candidate should demonstrate:

• The ability to engage confidently with non‑technical stakeholders.
• A structured approach to turning broad business challenges into clear requirements and deliverable solutions.
• Strong communication, facilitation, and presentation skills.
• A proactive and consultative working style.
• A strong focus on adoption and measurable outcomes, not only technical completion.

Advantageous Experience:

The following would be beneficial:

• Retail industry experience.
• Experience establishing an intake, prioritisation, or governance process for AI initiatives.
• Experience helping an organisation move AI solutions from experimentation into repeatable, governed delivery.

Personal Attributes

The ideal candidate will be:

• Curious and commercially minded.
• Comfortable working with ambiguity.
• Pragmatic and delivery focused.
• Collaborative, credible, and confident with stakeholders at different organisational levels.
• Comfortable taking ownership of an initiative from discovery through delivery and adoption.

Preference will be given to candidates who will enhance the diversity of the team, aligned to our Employment Equity plan.