Software Engineer II - Backend/Platform Agentic AI

About the role

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.

Responsibilities

• Build and operate services delivering AI-powered features to customers, ensuring correctness, performance, and reliability in a multi-tenant, customer-facing platform.
• 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.

Requirements

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), 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.

Skills

• 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).

Benefits

Competitive base salary, annual bonus or commissions, 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.