AI & Platform Engineer at Kifiya Financial Technology

What You’ll Do

• Design, implement, and optimize AI/ML infrastructure (model deployment pipelines, feature stores, monitoring).
• Build and maintain cloud-native, containerized, distributed systems for high-volume data and AI workloads.
• Develop APIs, microservices, and integrations to embed AI-driven decisioning into core systems.
• Ensure robust monitoring, logging, reliability, security, and scalability of models in production.
• Partner with Data Science, Data Engineering, and Credit Risk to accelerate AI solution delivery.
• Evaluate emerging AI tools, frameworks, and platforms to strengthen the tech stack.
• Implement best practices for compliance, explainability, and responsible AI.

What You’ll Bring

• Bachelor’s or Master’s in Computer Science, Engineering, or related field.
• 3–5 years in AI/ML engineering, platform engineering, or software engineering with data-intensive systems.
• Strong programming in Python, Java, or Scala; proficiency with TensorFlow, PyTorch, or Scikit-learn.
• Hands-on with ML lifecycle tools (MLflow, Kubeflow, SageMaker, Vertex AI, etc.).
• Expertise in cloud (AWS/Azure/GCP), Docker/Kubernetes, and CI/CD pipelines.
• Experience with data infrastructure (Spark, Kafka, Databricks, or equivalent).
• Knowledge of MLOps/DevOps and modern API design.
• Strong problem-solving and cross-functional collaboration skills.
• Experience in fintech, financial services, or credit risk.
• Exposure to XAI, model monitoring, and regulatory compliance frameworks.
• Familiarity with OLAP engines, data warehouses, and real-time decisioning platforms.