Lead AI Engineer
Mastercard · Gurgaon, India
Mastercard is hiring a Lead AI Engineer in Gurgaon.
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 Engineer
Requirements
- Master’s degree with 3+ years of relevant experience, or Bachelor’s degree with 5+ years, in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field; equivalent practical experience considered.
- Hands-on MLOps experience across model monitoring, feature catalogs, experiment tracking, model registry, and lifecycle CI/CD pipelines.
- Hands-on experience administering Databricks workspaces, including cluster and compute policies, job orchestration, runtime and library upgrades, permissions, and secrets.
- Experience deploying and maintaining infrastructure through infrastructure as code and automated pipelines, including environment provisioning, configuration management, and controlled release and rollback.
- Strong experience with Spark and distributed data processing.
- Proficiency in Python, PySpark, and SQL.
- Hands-on experience with CI/CD and build tooling such as Git, Jenkins, Maven, and Artifactory.
- Experience building and optimizing feature engineering and large-scale data processing workflows.
- Strong understanding of machine learning and deep learning techniques, model lifecycle management, and production AI systems.
- Experience with model deployment, evaluation, observability, optimization, and operational support.
- Experience with cloud operations across public and private cloud environments.
- Ability to communicate technical concepts clearly, work independently, and mentor other engineers.
Preferred qualifications
- Experience with MLOps tools such as MLflow, Comet, or Weights and Biases.
- Experience automating Databricks administration and deployment with the Databricks CLI, REST APIs, Asset Bundles, or the Databricks Terraform provider.
- Experience with infrastructure as code and configuration tooling such as Terraform or Ansible, and with Docker and Kubernetes.
- Experience contributing to engineering standards, governance frameworks, or observability practices for production AI systems.
- Experience with Generative AI, LLMs, RAG, or agentic AI applications.
- Familiarity with AI-assisted development tools such as GitHub Copilot or Claude Code.
- Experience with data governance tooling, including data catalogs, lineage, role-based access control, and sensitive data handling.
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.
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;
About Mastercard
AI Solutions, part of Mastercard’s AI & Data organization, scales AI across the enterprise, moving use cases beyond pilots into trusted, production-grade capabilities embedded in Mastercard’s platforms and products. Centralizing this capability drives speed to scale, operational resilience, consistent delivery standards, and responsible AI by design, in close partnership with the AI Center of Excellence. This position sits on the Horizontal Enablement team, reporting to the Manager, AI Engineeri