AI Graduate Engineer Programme at Ubundi

Ubundi is currently seeking an ambitious and innovative AI Graduate Engineer to join their forward-thinking engineering team in Stellenbosch, Western Cape. As a human-centred AI venture studio in South Africa, Ubundi creates proprietary products, assists enterprise clients in deploying operational artificial intelligence, and leads an active robotics practice. This role offers an unprecedented opportunity for a recent graduate or final-year student to step straight into the 0-to-1 build phase, architecting real-world AI applications, custom agents, and high-impact automation systems.

Key Responsibilities

• Work with an AI-first mindset across all engineering, workflow development, and problem-solving initiatives.

• Architect and develop rapid software prototypes for technical feasibility testing and early validation.

• Build, optimize, and deploy internal and client-facing AI systems and automation pipelines.

• Design rigorous evaluation frameworks to benchmark and enhance the quality and reliability of AI-generated outputs.

• Clean, structure, and process messy real-world datasets into usable training and retrieval pipelines.

• Experiment extensively with advanced prompt engineering, autonomous agents, modern workflows, and Retrieval-Augmented Generation (RAG) architectures.

• Collaborate directly with founders, engineers, and industry advisors to explore novel business ideas and technical solutions.

Why Join the Company

Joining Ubundi provides direct exposure to the frontier of generative AI, automation, and robotics within a high-trust, high-autonomy venture studio. Backed by experienced founders who have scaled global tech businesses such as WooCommerce, Conversio, and Cogsy, you will experience rapid professional growth without corporate red tape. Ubundi champions a culture rooted in Ubuntu—prioritizing craft, curiosity, daylight experimentation, and work-life harmony. The role offers flexible hybrid work arrangements centered around their collaborative engineering hub in Stellenbosch.

Application Strategy (Exclusive)

• Showcase Hands-On Projects: Highlight personal coding projects, hackathon prototypes, or hobbyist AI workflows in your CV—especially tools built using LLMs, APIs, or open-source AI models.

• Demonstrate Full-Stack Curiosity: Emphasize your ability to write clean code across both frontend and backend environments, proving you are comfortable learning new frameworks rapidly.

• Articulate Problem-Solving Mindset: Tailor your cover letter to articulate how you think through messy data challenges and iterate when standard documentation or clear paths are absent.

Interview Preparation

Candidates shortlisted for technical evaluation should prepare for the following interview prompts:

• "Can you walk us through an AI tool, script, or model you experimented with recently, detailing the architecture, challenges faced, and how you evaluated output quality?"

• "How do you approach structuring and indexing unstructured datasets when building a Retrieval-Augmented Generation (RAG) pipeline?"

Sharpen your responses and practice technical scenarios using the Xhosadev Interview Simulator before your interview.

How to Apply

Interested applicants should apply directly online. Please ensure your submission includes an updated portfolio, GitHub link, or detailed description of an AI-powered tool or project you have developed.

Please apply using the Quick Apply button on this page.

• Recent graduate or final-year student completing a Bachelor's degree in Computer Science, Engineering, Mathematics, Information Systems, or a related quantitative field.

• Demonstrated experience building software applications, side projects, hackathon prototypes, or freelance technical solutions.

• Practical exposure to AI developer tools, APIs, LLM integrations, and modern automation frameworks.

• Solid foundation in programming, with the ability to write and review code across frontend and backend systems.

• High curiosity, self-direction, and comfort navigating ambiguous, fast-moving technical challenges.

• Familiarity with machine learning, data engineering, data cleaning, or prompt engineering is an advantageous bonus.