Senior AI Engineer: Agentic Systems & Production ML

Mastercard Inc.; Ciudad de México; Presencial; MXN 900.000 - 1.400.000; Jornada completa

Descripción de la vacante

Mastercard Inc. is seeking a Senior Software Engineer (AI) to lead the design and delivery of agentic applications that reason, orchestrate tools, and interact with enterprise systems. You will collaborate with Applied AI, Data Science, Product, Security, and Platform teams to move from concept to production.

The role emphasizes hands-on architecture, secure cloud-native services, and scalable, observable systems while applying responsible AI practices throughout the SDLC.

Formación

• Bachelor’s degree in computer science, software engineering, or related field.
• +10 years of software engineering experience building scalable systems.
• Hands-on experience building and shipping AI-powered products or agentic apps.
• Strong agentic system design: planning, reasoning, workflows.
• Production deployment focus on reliability, security, and governance.
• Proficient in Java or Python and modern cloud-native stacks.
• Experience with cloud platforms: Kubernetes, AWS/Azure/GCP.

Responsabilidades

• Lead hands-on architecture and delivery of agentic AI services.
• Define patterns for production AI systems, including guardrails and cost control.
• Drive end-to-end SDLC from discovery to production operations.
• Improve developer workflows, testing, and release confidence.
• Collaborate with Product, Applied AI, Data Science, and stakeholders.
• Mentor engineers and ensure security and reliability.

Conocimientos

LLM-based workflows

Java

Python

Kubernetes

React

Educación

Bachelor's degree in Computer Science

Herramientas

Kubernetes

AWS

Azure

GCP

Next.js

React

Descripción del empleo

Mastercard Inc. is seeking a Senior Software Engineer (AI) to lead the design and delivery of agentic applications that reason, orchestrate tools, and interact with enterprise systems. You will collaborate with Applied AI, Data Science, Product, Security, and Platform teams to move from concept to production.

The role emphasizes hands-on architecture, secure cloud-native services, and scalable, observable systems while applying responsible AI practices throughout the SDLC.