LLMOps Engineer

About ALX Africa

ALX Africa, a non-profit organisation under the ALX Foundation, is dedicated to unlocking the potential of Africa's digital future. Formerly part of Sand Tech Holdings, we've embarked on an independent journey to provide world-class tech skills training and career acceleration programmes. Our mission is to bridge the digital divide, upskill and re-skill talent, and create a generation of innovative leaders. By 2030, we aim to empower 2 million Africans to secure sustainable tech careers.

With hubs in 8 cities across Africa and counting, we provide safe access to quality learning and a dedicated network of expert instructors. Our innovative programmes equip learners with the practical skills and knowledge needed to succeed in today's rapidly evolving tech industry. Through a combination of rigorous coursework, industry partnerships, and hands-on projects, we prepare our students for in-demand roles in software engineering, data science, and cybersecurity.

We achieve this by:

Providing young professionals with access to the most in-demand tech skills that will power the future.

Empowering the next generation of technology innovators, entrepreneurs, and business leaders through challenging, real-world coursework.

Building a lifelong, impactful community of tech professionals that support them at all stages of their career journey.

Our impact thus far:

347k+ graduates since 2020

257k youth in work

31k youth starting own ventures

60k youth in jobs created by entrepreneurs

Visit our website www.alxafrica.com to learn more about our digital revolution.

Role Summary

Project A is ALX’s AI learning platform — a set of LLM products used by learners. Every one generates a stream of LLM data, and every one has hypotheses baked into it about what “working” means. The LLMOps Engineer owns the analyzer function: turning that stream into an honest answer about whether the products work. Take RAG as one example — documents must be stored accurately, fetched accurately, and fetched in the right mixture: three separate failure modes, each needing its own eval. Every product decomposes like that. This is a junior-to-mid role with a deliberate growth path: you start close to the technical lead’s designs and grow into full ownership of the function. You will work in collaboration with Anthropic Engineers, a cross functional team of AI engineers, product managers and data scientists to design world class learning experiences.

Specific Responsibilities

Evaluation Suites

Build and run eval suites per product, decomposed by failure mode, running on schedule and on every release — regression testing so nothing ships if it broke what worked.

Keep evals cost-effective as the product line grows.

Reporting, Data & Collaboration

Own the reporting loop — findings from evals and platform data in front of the team and stakeholders, including surfacing unintended or problematic model behaviour before learners do.

Steward the core datasets the team depends on, including classified customer-support data.

Partner with the AI Product Manager on instrumentation — they instrument the product, you build the evals over what is captured. This is a measurement role, not infrastructure — no model hosting or serving.

Skill Requirements - Essential