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AI Engineer
FlutterwaveAI Engineer responsible for designing and deploying AI systems in payment infrastructure. Focus on payment investigation and reliability improvements in a fintech environment.
Tech Stack
Tools & technologiesDockerKubernetesPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Design and deploy production-grade AI systems embedded into payments infrastructure
- Build and productionize a locally hosted AI system for payment failure investigation
- Develop LLM-powered agent for autonomous payment failure analysis
- Build internal LLM infrastructure with no external API dependency
- Generate structured pipelines for root cause identification across transaction failures
- Automate Level 1 incident investigations
- Optimize model performance to reduce Mean Time to Resolution (MTTR)
- Build reusable internal AI infrastructure and scalable pipelines
- Deploy AI into operational workflows with measurable efficiency improvements
- Implement version-controlled datasets, model versioning, and automated drift detection
Requirements
What you’ll need- 4–7+ years in Machine Learning / AI Engineering
- Strong Python proficiency (PyTorch, TensorFlow, Hugging Face)
- Experience working with LLMs (fine-tuning, RAG, embeddings, retrieval systems)
- Experience deploying ML systems in production (Docker, Kubernetes, CI/CD)
- Experience building inference pipelines and monitoring systems
- Strong understanding of evaluation metrics and ML governance practices
- Experience working with large-scale structured and unstructured datasets
- Strong preference for previous fintech or payments experience
Benefits
Comp & perks- Health insurance
- Professional development opportunities
ATS Keywords
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Hard Skills & Tools
Machine LearningAI EngineeringPythonPyTorchTensorFlowHugging FaceLLMsinference pipelinesevaluation metricsML governance
Soft Skills
problem-solvinganalytical thinkingcommunicationcollaborationadaptabilityattention to detailtime managementcritical thinkingcreativityleadership