Entry Level Mastercard Software Engineer Jobs in Washington, DC

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build asustainableeconomy where everyone can prosper. We support a wide range of digital payments choices, making transactionssecure, 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

Software Engineer II - Backend/Platform Agentic AIWho is Mastercard?
Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
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
#AI1Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

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.

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