Senior / Lead AI Engineer

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Senior / Lead AI Engineer

Lead AI Engineer - Foundry R&D, Singapore

We are looking for a Lead AI Engineer to join the Mastercard Foundry R&D team. You will help explore new technologies and build scalable AI solutions. The ideal candidate is hands-on, curious, analytical, and motivated to experiment in a fast-paced innovation environment.

What you'll do

* Drive generative AI innovation: Lead design and development of AI prototypes, pilots, and MVPs. Build solutions using LLMs, transformers, and other generative techniques. Experiment rapidly to test new ideas and expand AI use cases in payments and commerce.
* Provide technical leadership: Guide a small engineering team through the full development lifecycle. Translate requirements into designs, write clean and tested code, and ensure production-ready quality. Mentor team members and promote strong engineering practices.
* Collaborate across teams: Work with product owners, data scientists, researchers, and platform engineers to identify opportunities and deliver solutions. Align with global teams and integrate generative AI features into existing systems.
* Model deployment and integration: Oversee deploying AI models to production and integrating them with applications and data systems.
* R&D and continuous learning: Stay current on AI and generative AI trends. Explore new model architectures and automation techniques. Evaluate emerging tools and promote responsible use of advanced AI methods.

What you'll bring

* Proven leadership: Experience leading software or AI/ML teams in an agile environment. Able to coordinate complex work, delegate effectively, and maintain high engineering standards.
* Technical breadth and depth: Strong full-stack and system design experience. Able to build backend services and integrate AI features into real products. Knowledge of data engineering and cloud infrastructure is a plus.
* AI/ML expertise: Hands-on experience developing and deploying ML and generative AI models. Familiarity with LLMs, transformers, and neural networks. Skilled with frameworks such as PyTorch or TensorFlow. Understanding of data processing, feature engineering, and model evaluation.
* Agile mindset with focus on quality: Strong grasp of modern engineering practices, including CI/CD, automated testing, and code review.
* Innovative thinking: Comfortable experimenting with new ideas and using advanced AI techniques such as RAG or knowledge-grounded models.
* Communication and collaboration: Strong written and verbal communication skills. Able to explain complex topics clearly and work with diverse stakeholders.

Required skills

* Education and experience: Bachelor's or Master’s degree in Computer Science or related field. 8–12+ years of software development experience, including 2+ years in technical leadership roles involving AI/ML.
* Programming and engineering: Strong Python skills for ML tasks and experience with languages such as Java or Node.js for building production systems. Solid understanding of algorithms, data structures, and system design.
* AI/ML technologies: Hands-on experience with ML frameworks, classical ML libraries, NLP tools, and transformer models. Experience fine-tuning or adapting large models and implementing chatbots, recommender systems, or computer vision applications. Familiarity with orchestration frameworks such as LangChain or LlamaIndex.
* Cloud and MLOps: Experience deploying models on AWS, Azure, or GCP. Familiar with MLOps practices such as automated testing, monitoring, model versioning, and observability. Experience with containers and microservices.
* Analytical skills: Ability to troubleshoot data quality, model drift, and performance issues.
* Collaboration and leadership: Strong communication skills, ability to mentor team members, and experience working with cross-functional teams. Comfortable balancing rapid experimentation with sound engineering.

Preferred skills

* Advanced AI specializations: Experience with GANs, VAEs, or knowledge-grounded AI. Familiarity with techniques to reduce hallucination and improve groundedness.
* Tooling and frameworks: Experience building RAG pipelines, using vector databases, embeddings, or semantic search. Familiar with agent-based AI workflows or emerging GenAI tools.
* Full-stack and product integration: Familiarity with modern frontend frameworks or mobile development. Ability to build end-to-end demos showcasing generative AI features.
* Domain knowledge: Experience in payments, fintech, or enterprise systems. Understanding of regulatory, security, and compliance needs in AI development.
* Higher degree or research experience: A Master’s or PhD in ML/AI is a plus. Publications, patents, or research contributions are valued. Active involvement in AI communities is beneficial.

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard’s security policies and practices;

• Ensure the confidentiality and integrity of the information being accessed;

• Report any suspected information security violation or breach, and

• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.