Key skills
GraphQLJavaPythonSpringSpring BootSpringBootCAIMLGenerative AILLMOpenAIRAGLangChainLlamaIndexPineconeDockerCollaboration
About this role
Role Overview
- FlexiSAF is a leading EdTech company driving innovation in education across Africa.
- Launching a specialized AI Engineering Training and Internship Program designed to equip passionate software developers with the skills and hands-on experience needed to transition into full-fledged AI Engineers.
- Over four intensive months, participants will learn to design and build intelligent, LLM-powered applications using modern frameworks such as LangChain, Retrieval-Augmented Generation (RAG) and vector databases.
- Emphasis on practical, project-based learning; from implementing AI-driven workflows and chatbots to integrating models into production-ready applications.
- Trainees will also gain exposure to Spring Boot for enterprise API integration and containerization for scalable deployments.
- Ideal candidates are curious, driven individuals with a strong foundation in programming who are eager to explore the fast-evolving world of Generative AI.
- Upon successful completion, participants will be well-positioned to take on AI Engineering roles within any organization building intelligent products and systems.
Requirements
- Strong Python programming skills, especially in AI/ML contexts.
- Basic understanding of LLMs and prompt engineering.
- Familiarity with LangChain or willingness to learn quickly.
- Basic knowledge of vector databases like FAISS or Pinecone.
- Understanding of RAG pipelines and embedding concepts.
- Experience working with APIs (REST, GraphQL).
- Exposure to frontend or backend development.
- Familiarity with Java and Spring Boot.
- Strong problem-solving and debugging skills.
- Ability to learn new tools and frameworks rapidly.
- Minimum Qualification: High School (S.S.C.E).
Tech Stack
- GraphQL
- Java
- Python
- Spring
- Spring Boot
- SpringBoot
Benefits
- Hands-on Learning: Work on real AI challenges, from simple automation scripts to production-grade intelligent systems.
- Industry-Relevant Tools: Gain experience with LangChain, RAG, LlamaIndex, OpenAI API, Spring Boot, and Docker—tools shaping the future of AI development.
- Capstone Portfolio Projects: Build a project portfolio demonstrating your end-to-end AI engineering capabilities.
- Mentorship & Collaboration: Learn alongside experienced engineers and mentors who guide you through practical problem-solving.
- Career Readiness: Graduate with the skills and confidence to take on AI Engineering roles within our organization or similar high-growth companies.
- Certification of Completion: Participants who meet performance expectations will receive a program certificate endorsed by the organization.