Lead 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 Lead AI Platform Engineer Overview We’re looking for a self-motivated and enthusiastic Lead AI Platform Engineer to be on the forefront of driving the development and deployment of enterprise-grade AI solutions using both low-code and pro-code platforms. This role will lead a high-impact team focused on translating business needs into intelligent, scalable systems that integrate seamlessly with enterprise infrastructure. The ideal candidate brings deep technical expertise, a collaborative mindset, and a passion for innovation—guiding solution design workshops, aligning AI capabilities with strategic goals, and delivering measurable value across the organization. About The Role- Development: Lead and mentor a team of AI engineers in developing and deploying end-to-end AI solutions using low-code tools (e.g., Microsoft Copilot Studio, Power Platform) and pro-code platforms (e.g., Databricks, AWS, Azure, etc.)
- Integration: Architect and enable AI solutions and data pipelines that integrate seamlessly with enterprise systems, ensuring scalability, security, and performance
- Design: Drive technical discovery sessions and solution design workshops with stakeholders to capture requirements and translate business needs into technical solutions.
- Deployment: Enable and lead deployments of prototypes, proofs of concept, and production-grade AI models and applications
- Optimization: Enhance the scalability and modularization of platform components to facilitate easy integration of new domains and models
- Cloud Management: Manage cloud-based AI services and containerized environments, ensuring the reliability, security, and scalability of AI infrastructure
- Collaboration: Work closely with AI Deployment and AI/ML Feature Engineers to ensure cohesive platform development
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Significant hands-on experience in developing and deploying AI solutions with low-code or pro-code tooling in production environments
- Technical Skills:
- Proficiency in low-code (e.g., MSFT Power Platform, Copilot Studio, etc.) and pro-code (e.g., AWS, Databricks, etc.) tools and practices tailored for AI/ML systems.
- Experience with containerization technologies such as Docker and Kubernetes.
- Strong understanding of cloud platforms (AWS, Azure) and their AI/ML services.
- Knowledge of monitoring and alerting tools specific to ML performance.
- Familiarity with data validation, drift detection, and automated testing frameworks
- Experience using RPA and developing AI solutions
- Hands-on experience with AI/ML feature engineering and data pipeline optimization.
- Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment
- Technical Expertise: Deep understanding of AI/ML deployment processes and best practices.
- Collaboration: Ability to work effectively with cross-functional teams, including data scientists, engineers, and platform teams.
- Communication: Excellent verbal and written communication skills to articulate technical concepts to non-technical stakeholders.
- Adaptability: Ability to adapt to changing technologies and learn new skills quickly.
- Problem-Solving: Strong analytical and problem-solving skills to address complex deployment challenges
- 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.
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