AI Engineer

About the role

Flutterwave, one of Africa’s largest payment technology companies, is hiring an AI Engineer to build production-grade AI systems embedded in its payments infrastructure. The primary mandate is to develop a locally hosted LLM-powered agent for autonomous payment failure investigation, cutting manual operational load and improving payment reliability across its pan-African network. The role is full-time and based in Lagos, with a remote option for qualified candidates. Required experience: 4 to 7 years in machine learning or AI engineering. No application deadline listed; apply now.

Responsibilities

• Design and deploy a locally hosted LLM-powered agent for autonomous payment failure analysis, with no external API dependencies for core production workflows.
• Build scalable training and inference pipelines and reusable model components that other teams can extend.
• Deploy at least two additional AI use cases across the payments platform, such as chatbot support, automated reporting, or issue clustering.
• Maintain 99.9% production uptime with defined inference latency targets and a structured model retraining cadence.
• Implement AI governance: version-controlled datasets and models, evaluation benchmarks, automated drift detection, and documented architectures that meet privacy and compliance standards.

Requirements

• Bachelor’s degree or equivalent in computer science, software engineering, or a related field.
• 4 to 7 years of hands-on experience in machine learning or AI engineering in production environments.
• Proven ability to train, deploy, and monitor production-grade models in high-availability systems.
• Experience building or deploying LLM or NLP systems; familiarity with open-source inference stacks (Llama, Mistral, vLLM, or similar).
• Strong Python skills and proficiency with ML frameworks such as PyTorch or HuggingFace Transformers.

Nice to have

• Prior work in fintech, payments infrastructure, or other high-availability financial systems.
• Experience with model compression for resource-constrained deployment: quantization, pruning, or distillation.
• MLOps tool experience: MLflow, DVC, Weights and Biases, or equivalent for experiment tracking and model versioning.
• Familiarity with local GPU infrastructure setup and management for self-hosted inference.

How to apply

Apply through the link above on MyJobMag, or visit Flutterwave’s official careers portal at careers.flutterwave.com. Submit a CV and a short cover note (max one page) describing your experience with LLM deployment and autonomous AI agents in production. Shortlisted candidates will be contacted for an initial technical screen.