At DigiPay, we are building AI-driven capabilities that power the future of payments and customer experience for millions of users. With access to rich, high-volume transactional data and mission-critical financial systems, AI and machine learning are essential to delivering intelligent, reliable, and secure digital finance products.
We are looking for an AI Engineer who can turn complex fintech challenges into scalable, production-ready AI and data-driven solutions. What matters most is your ability to build, collaborate, iterate quickly, and ship systems that create measurable business impact.

Responsibilities:

• Design, build, and maintain end-to-end ML and AI systems for intelligent routing, customer behavior analysis, and operational automation.
• Apply machine learning, statistical modeling, and modern AI techniques to solve high-impact problems.
• Translate ambiguous business needs into well-defined AI opportunities and propose engineering solutions that are feasible, scalable, and aligned with company priorities.
• Own the full AI lifecycle: data processing, feature engineering, model development, evaluation, experimentation, deployment, optimization, and post-production monitoring.
• Work closely with product and engineering teams to build solutions that integrate seamlessly into DigiPay’s infrastructure.
• Evaluate and adopt new tools, frameworks, and algorithms when they provide clear and measurable improvements to reliability, scalability, or accuracy.
• Ensure production systems run efficiently at scale — balancing accuracy, latency, cost, and maintainability.
• Contribute to building internal AI/ML platforms, reusable pipelines, automation tools, and model governance workflows.

Requirements:

• Hands-on experience building and deploying production-grade ML or AI systems, ideally in high-scale or real-time environments.
• Solid understanding of ML development workflows, including data pipelines, evaluation frameworks, monitoring, and MLOps tools.
• Ability to make sound engineering decisions with partial information and operate effectively in fast-moving, high-ambiguity domains.
• Strong communication skills and a product-oriented mindset, focusing on practical, measurable outcomes.
• Curiosity, initiative, and a drive to stay ahead in the evolving AI and ML landscape.