MastercardSenior Software Engineer
Mastercard is hiring a Senior Software Engineer in Mexico City, Mexico. Level rates it ; you can apply on Mastercard.
Level's read on this job
- On Level's scale, this software engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions Python, Git and RAG among its tools and skills.
- Level classes it as a senior role.
- Mastercard has 967 other open roles on Level.
AI in this role
Build intelligent agentic applications and AI-enabled engineering platforms to accelerate product delivery.
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 Software EngineerOverviewThe CNPF Data & AI organization is looking for an exceptional Senior Software Engineer to help build the next generation of intelligent, agentic applications and engineering platforms. This is a high-impact role for a hands-on engineer who combines deep software engineering expertise with a passion for AI, innovation, and practical problem solving.
You will design and build scalable, production-grade systems that leverage AI, agentic workflows, and modern developers tooling to accelerate product delivery and improve engineering productivity across the full product development lifecycle. You will work at the intersection of software engineering, AI capability development, developer experience, and platform innovation—turning emerging technologies into secure, reliable, and reusable capabilities that create measurable business value.
Position Responsibilities
As a Senior Software Engineer, you will:
Software Design, Architecture & Development:
• Design, build, and evolve intelligent, agentic applications and platform capabilities that solve meaningful business problems at scale
• Apply robust software design principles, design patterns, and architectural best practices to create scalable, maintainable, and extensible systems
• Influence and contribute to system architecture decisions, including distributed systems, event-driven patterns, and cloud-native design
• Develop high-quality, well-structured, and efficient code leveraging strong data structures and algorithmic thinking
AI-Enabled Engineering & Innovation:
• Apply AI and agentic development patterns to improve engineering productivity across design, coding, testing, debugging, documentation, release engineering, and operational support
• Use modern tools and coding assistants thoughtfully to accelerate delivery while maintaining strong standards for quality, security, reliability, and maintainability
• Evaluate emerging AI tools, frameworks, and platforms and integrate them into engineering workflows where they create measurable value
Testing & Quality Engineering:
• Design and implement comprehensive testing strategies, including unit, functional, integration, and end-to-end testing
• Build and maintain automated testing frameworks and integrate them into CI/CD pipelines
• Ensure high levels of test coverage, system reliability, and defect prevention across the software lifecycle
• Leverage AI-assisted solutions to enhance testing efficiency and effectiveness
Code Quality & Engineering Excellence:
• Conduct and actively participate in code reviews, ensuring adherence to coding standards, maintainability, security, and best practices
• Champion engineering excellence, including clean code, reusable design, and continuous improvement practices
• Mentor peers through review processes and knowledge sharing
Performance, Security & Reliability:
• Design and optimize systems for performance, scalability, latency, and cost efficiency
• Apply and promote secure coding practices, integrating security considerations into all stages of development (DevSecOps)
• Ensure systems are observable, resilient, and production-ready, with strong monitoring, alerting, and incident response capabilities
Operability & Troubleshooting:
• Build systems with strong operational readiness, ensuring maintainability and supportability in production environments
• Diagnose and resolve complex technical issues across distributed systems, leveraging structured troubleshooting approaches
• Continuously improve system reliability through automation, root cause analysis, and proactive enhancements
Collaboration & Delivery:
• Partner with product, data science, and engineering teams to translate ideas into production-grade solutions with clear business impact
• Improve SDLC efficiency through automation, CI/CD, and AI-assisted workflows
• Lead by example through hands-on development, strong ownership, and execution
All About You
• You thrive on building innovative, scalable systems that solve real-world problems
• You combine strong engineering fundamentals (design, testing, algorithms) with curiosity for emerging AI technologies
• You take ownership of outcomes and consistently deliver high-quality solutions
• You balance speed with engineering rigor, ensuring systems are secure, reliable, and maintainable
• You are a strong collaborator who elevates team performance through communication, mentorship, and shared standards
• You embrace continuous learning and experimentation to push the boundaries of modern software engineering
Ideal Candidate Qualifications
• Strong programming skills in languages such as Java and/or Python, with demonstrated ability to write efficient, high-performance code using appropriate data structures and algorithms
• Hands-on experience building agentic or AI-enabled applications;
• Strong understanding of APIs, distributed systems, event-driven architectures, and enterprise integration patterns
• Intermediate experience with React or Next.js
• Experience with cloud-native development using Kubernetes and managed cloud platforms such as AWS or Azure
• Experience with CI/CD, automation, and engineering productivity tooling;
• Familiarity with modern AI frameworks, SDKs, and tools for building intelligent applications and agent workflow
• Proven experience building scalable, maintainable, production-grade systems
• Proven experience designing and implementing unit, functional, and integration testing strategies and frameworks
• Hands-on experience building applications or platforms using Generative AI or agentic design patterns
• Strong understanding of:
• Distributed systems and cloud-native architectures
• APIs, event-driven systems, and integration patterns
• AI system design trade-offs (latency, cost, reliability, safety, governance)
• Experience driving code quality through peer code reviews and engineering standards enforcement
• Experience taking AI-enabled solutions from prototype to production with strong engineering discipline across reliability, observability, performance, and security
• Experience improving SDLC through:
• CI/CD pipelines
• Automation and testing frameworks
• AI-assisted engineering workflows
• Experience with Kubernetes and cloud platforms (AWS, Azure)
• Familiarity with AI frameworks, SDKs, and tools (LLMs, RAG, embeddings, inference APIs)
• Education Requirements: Bachelor's degree is required, Master's degree is preferred.
Preferred Qualifications
• Familiarity with model evaluation, AI safety controls, and governance practices
• Experience building reusable developer platforms or internal engineering tools
• Practical use of AI coding assistants to improve delivery speed and quality;
• Familiarity with LLM orchestration, prompt and context management, memory patterns, inference APIs, embeddings, retrieval-augmented generation, vector databases, model evaluation, AI observability, and responsible AI controls.
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.
How we rate this
Senior Software Engineer at Mastercard rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $167k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a project where software engineering was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, AI Evaluation, AI Safety, and Software Engineering. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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