AI Engineer Fellowship (Remote – Africa Preferred) at Code for Africa (CfA)
Code for Africa (CfA), through the InclusionAI
Research Network, with the A+
Alliance, is offering a 6 month fellowship for an AI
Engineer, anywhere in the world, to join our TechLab in implementing
an AI Innovation Sandbox.
The AI Innovation Sandbox is funded by the International Development Research
Centre (IDRC) and the Foreign,
Commonwealth and Development Office (FCDO) designed to support
women-led and women-focused organisations across Sub-Saharan Africa to build
meaningful, ethical AI tools for their communities.
Through the fellowship, you will architect AI strategy and
implementation. You will own how we adopt, adapt, and deploy AI across multiple
products and those of our partner organisations. The core of this role is building
with AI: designing agent systems that do real work, engineering the context
that makes models useful, evaluating whether what you’ve built actually holds
up in the real world, and iterating until it does.
This is an AI Engineer role, not an ML Engineer role. We’re
looking for someone who builds systems and products using AI — with enough
understanding of how models work to make good decisions, not necessarily to
train them from scratch.
The successful candidates will work as part of a
multinational and multilingual team using digital collaboration tools to create
content for a global audience and international media partners.
Required: minimum requirements include:
- 4+
years building and shipping software, with meaningful hands-on experience
building AI-powered products or systems
- Fluency
in Python and TypeScript
- Demonstrated
experience designing and building agentic AI systems: multi-step task
execution, tool use, memory, planning, and error recovery
- Strong
context engineering instincts: you think about the full information
architecture a model needs to be useful, not just how to phrase a prompt
- A
systematic approach to evals: you design for measurability, not just
intuition, and you know how to tell whether an AI feature is actually
working
- Familiarity
with the broader AI ecosystem: open-source tooling alongside commercial
APIs and nonprofit access programmes from leading labs
- Strong
system design instincts around AI: you think about latency, fallbacks,
cost, and reliability, not just model quality
- Sound
judgement on responsible AI: bias, fairness, transparency, and the limits
of what a model should be asked to do
- The
ability to communicate clearly across the room: to an engineer debugging a
pipeline and to a journalist or funder asking what it all means
- Fluency
in English
- A
degree in Computer Science, Engineering, or a related field — or
equivalent experience you can point to through your work and portfolio
Preferred: candidates who are able to
demonstrate the following will have an advantage:
- Experience
deploying open-source LLMs in production environments
- Existing
relationships or experience working with AI lab programmes: Anthropic for
Startups/Nonprofits, OpenAI for Nonprofits, Google.org AI access, or
similar
- Familiarity
with vector databases, embedding models, and knowledge graph approaches
- Experience
with multimodal AI systems
- Background
in containerisation and cloud infrastructure (Docker, Kubernetes,
cloud-hosted model deployment)
- Experience
in civic technology, investigative journalism, international development,
or human rights contexts
- Experience
with multilingual NLP, particularly for low-resource or African languages
- Fluency
in French, Arabic, KiSwahili, or another major African language
- Experience
working across international, cross-cultural technical teams
Language and Location Requirements:
- Location:
Fully remote — open to candidates anywhere in the world, with a preference
for those based in Africa
- Languages:
English required; French, Arabic, KiSwahili, or any other major African
language is a significant advantage