Software Engineer II - AI-Driven Platform & Apps

Mastercard; Ciudad de México; Presencial; MXN 400.000 - 800.000; Jornada completa

Descripción de la vacante

Mastercard is seeking a Software Engineer II to design and implement intelligent, agentic applications and platform capabilities at scale. You will apply strong software engineering fundamentals to build secure, measurable, AI-powered solutions that boost engineering productivity across the lifecycle.

You will collaborate across product and data science teams, leverage Kubernetes and cloud platforms (AWS/Azure), and contribute to testing, deployment, and observability practices to deliver

Formación

• Proficient in Java and/or Python with strong data structures and algorithms.
• Hands-on experience with agentic or AI-enabled applications.
• Understanding of APIs, distributed systems, event-driven architectures.
• Experience with Kubernetes and cloud platforms (AWS, Azure).
• Familiarity with CI/CD, automation, and engineering productivity tooling.
• Knowledge of AI frameworks, SDKs, and tools for building intelligent applications.
• Experience taking AI-enabled solutions from prototype to production with strong discipline.

Responsabilidades

• Design, build, and evolve intelligent, agentic applications and platform capabilities at scale.
• Apply robust software design principles and architectural patterns.
• Influence system architecture decisions including distributed systems and cloud-native design.
• Develop high-quality, efficient code and ensure security, reliability, and maintainability.

Conocimientos

Java

Python

Distributed systems

CI/CD

React/Next.js

Cloud-native

Herramientas

Kubernetes

AWS

Azure

CI/CD tooling

Descripción del empleo

Mastercard is seeking a Software Engineer II to design and implement intelligent, agentic applications and platform capabilities at scale. You will apply strong software engineering fundamentals to build secure, measurable, AI-powered solutions that boost engineering productivity across the lifecycle.

You will collaborate across product and data science teams, leverage Kubernetes and cloud platforms (AWS/Azure), and contribute to testing, deployment, and observability practices to deliver