Senior Software Engineer (AI)
Mastercard3 days ago
Mexico City, MexicoSenior
Responsibilities
- Lead the architecture, design, implementation, testing, release, and operation of agentic applications, AI-powered services, and platform capabilities.
- Define production AI engineering practices covering evaluation, monitoring, guardrails, resiliency, cost control, rollback, reliability, and governance.
- Improve AI-enabled software development workflows, including automation, test generation, code review quality, release confidence, and developer productivity.
- Build highly available, secure, maintainable cloud-native services with strong observability, performance, and operational readiness.
- Partner with Product, Applied AI, Data Science, Security, Platform, and business stakeholders to translate opportunities into scalable product capabilities.
- Provide technical leadership through architecture decisions, design reviews, code reviews, hands-on contribution, mentoring, and roadmap development.
- Create reusable platforms, frameworks, and internal engineering capabilities that improve developer experience and accelerate delivery.
Requirements
- Bachelor’s degree in computer science, software engineering, or a related technical field is required; an advanced degree is preferred.
- 10+ years of software engineering experience building scalable, secure, maintainable production systems and leading complex technical initiatives end to end.
- Hands-on experience building and shipping AI-powered products or agentic applications using LLMs, orchestration frameworks, tool-calling patterns, retrieval, and context-aware workflows.
- Strong understanding of agentic system design, including planning, reasoning loops, workflow orchestration, memory, grounding, evaluation, safety, and human-in-the-loop controls.
- Experience taking AI solutions from prototype to production with attention to reliability, observability, latency, cost, security, and governance.
- Strong programming skills in backend languages such as Java or Python and the ability to produce high-quality, tested, production-ready code.
- Experience with Kubernetes and managed cloud services on AWS, Azure, or GCP.
- Understanding of APIs, distributed systems, event-driven architectures, data pipelines, and enterprise integration patterns.
- Experience with automated testing, DevSecOps, engineering automation, and AI coding or engineering assistants.
- Strong software security background, including authentication, authorization, secrets management, encryption, threat modeling, and secure deployment practices.
- Front-end experience with React and/or Next.js is beneficial.
- Strong collaboration, communication, product judgment, and ability to influence engineering, product, data science, and leadership stakeholders.
Tech Stack
Categories
About Mastercard
Mastercard builds and operates a global payments network used by banks, merchants, fintechs, and governments, offering card processing, real-time payments, tokenization, and fraud/risk services. It generates revenue from transaction processing and assessment/service fees across more than 200 countries and territories. Founded in 1966 and headquartered in Purchase, New York, Mastercard is a public company listed on the NYSE (ticker: MA).