Title and Summary

Software Engineer II - Backend/Platform Agentic AI

Overview:
The Portfolio Intelligence (PI) program within Mastercard's Business & Market Insights (B&MI) division delivers analytics products that help financial institutions understand and grow their card portfolios. We're building a first-party AI platform that brings agentic, conversational, and generative AI capabilities directly into our products; powering features like natural-language analytics, automated report summaries, and personalized dashboard experiences for thousands of customers worldwide.

This is a builder role. You will write code daily, own components end-to-end, and ship production-grade AI-enabled services within a multi-tenant, customer-facing platform. You'll work alongside senior engineers, architects, and product partners to implement agentic workflows, integrate LLM-powered capabilities into our existing Java/Spring Boot stack, and help operate AI systems in production.

About the Role:
• Build and operate services delivering AI-powered features to customers, ensuring correctness, performance, and reliability in a multi-tenant distributed environment
• Implement agentic workflows and LLM integrations from design specifications, including tool calling, retrieval patterns, prompt management, and streaming responses
• Own delivery end-to-end: design, development, testing, deployment, documentation, and production support
• Contribute to CI/CD pipelines, automated testing, and release processes to ensure consistent, reliable delivery
• Monitor, debug, and improve AI systems-resolving production issues, optimizing latency, and maintaining service health
• Collaborate with senior engineers and platform teams to integrate PI-specific capabilities into shared AI infrastructure
• Follow and contribute to engineering best practices for code quality, testing, observability, security, and reliability
• Ensure adherence to Mastercard standards for AI governance, Responsible AI, and data security in a regulated environment

All About You:
• Experience building and shipping AI-powered features in production environments
• Strong Java engineering background, including building and maintaining Spring Boot microservices
• Hands-on experience in applied AI/ML (LLM integration, RAG pipelines, agentic workflows, model serving, or inference services)
• Familiar with production operations, including service ownership, incident response, and observability
• Solid testing discipline with experience in unit and integration testing
• Strong communication skills and ability to collaborate across distributed teams
• Proactive ownership mindset-asks thoughtful questions, learns quickly, and improves from feedback and production insights
• Motivated to grow AI engineering expertise and take on increasing technical scope over time

Required skills to be considered:
• Strong proficiency in Java for backend and service development
• Experience integrating AI/ML capabilities in production (LLM APIs, model serving, retrieval pipelines, or similar)
• Strong understanding of REST APIs, microservices architecture, and distributed systems fundamentals
• Experience with CI/CD practices, including branching, build automation, quality gates, and deployment pipelines
• Working knowledge of production operations: logging, metrics, monitoring, and incident response
• Experience with cloud platforms (AWS or Azure)

Nice-to-have:
• Python experience for AI/ML scripting, experimentation, or tooling
• Familiarity with agentic AI frameworks (LangGraph, LangChain, or similar)
• Experience with Databricks, Snowflake, or similar cloud data platforms
• Experience with RAG patterns, vector databases, or semantic search
• Exposure to prompt engineering and commercial LLM APIs (OpenAI, Anthropic, Azure OpenAI)
• Experience with Kubernetes, Docker, or container orchestration
• Familiarity with analytics platforms, data pipelines, or BI tools
• Experience in financial services or other regulated environments

#AI1

In line with Mastercard's total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.

Pay Ranges
Arlington, Virginia: $106,000 - $169,000 USD