Senior 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 AI Engineer

Overview

As a Senior AI Engineer within Mastercard's AI Center of Excellence, you will be responsible for designing, building, deploying, and operating enterprise-grade AI and Agentic AI solutions that drive innovation across Mastercard's products, platforms, and internal business functions. You will partner with data scientists, software engineers, architects, product teams, and business stakeholders to transform AI research and prototypes into secure, scalable, and production-ready solutions

You will be part of a team leading the engineering of AI platforms and applications, establish best practices for MLOps and AgenticOps and ensure AI systems meet Mastercard's standards for reliability, architecture, security, governance, and compliance

Key Responsibilities

- Design, develop, and deploy scalable AI, machine learning and Agentic AI applications for enterprise use cases
- Lead the productionization of AI solutions, transforming PoCs into highly available, resilient, and maintainable production systems
- Build E2E AI pipelines including data ingestion, feature engineering, model training, evaluation, deployment, monitoring, and continuous improvement
- Develop and deploy LLM-powered applications using RAG, AI agents, vector databases, prompt engineering, and model orchestration frameworks
- Design cloud-native AI architectures leveraging containerization, Kubernetes, serverless technologies, and event-driven microservices
- Implement MLOps and AgenticOps best practices, including CI/CD, automated testing, model versioning, observability, drift detection, governance, and rollback strategies
- Optimize AI models for scalability, latency, throughput, reliability, and cost efficiency in production environments
- Collaborate with platform engineering teams to build reusable AI services, APIs, SDKs, and enterprise AI capabilities
- Ensure AI solutions adhere to Mastercard's security, architecture, privacy, compliance, and Responsible AI standards
- Evaluate emerging AI technologies and recommend adoption strategies to accelerate enterprise AI innovation.
- Partner with cross-functional teams to define technical roadmaps and deliver AI capabilities aligned with strategic business objectives


Required Qualifications

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field
- Extensive experience building and deploying production AI/ML systems in enterprise environments
- Strong software engineering skills using Python, Java, or similar programming languages
- Experience developing cloud-native applications on AWS, Azure, or Google Cloud Platform
- Hands-on experience with containerization and orchestration technologies such as Docker and Kubernetes
- Strong understanding of distributed systems, APIs, microservices, and event-driven architectures
- Experience implementing CI/CD pipelines and MLOps frameworks for automated model deployment and lifecycle management
- Experience with modern AI frameworks such as PyTorch, TensorFlow, Scikit-learn, LangChain, LangGraph, LlamaIndex, or equivalent
- Experience deploying LLMs, RAG, vector databases, and AI agent frameworks
- Knowledge of model monitoring, observability, performance optimization, and AI governance.
- Strong communication and stakeholder management skills with the ability to influence technical decisions


What You'll Deliver

- Enterprise-scale AI and Generative AI solutions operating reliably in production.
- Production-ready AI platforms that enable reusable capabilities across Mastercard.
- Robust MLOps and AgenticOps practices that accelerate AI delivery while maintaining quality, security, and governance
- High-performance AI services that improve customer experiences, operational efficiency, and business outcomes across Mastercard

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.