Software Engineer II - Backend/Platform Agentic AI

Mastercard
Arlington, VA, United States
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Artificial Intelligence Amazon Web Services Business Analytics Applications Build Automation Automation of Tests Unit Testing Microsoft Azure Software Quality Continuous Integration Data Security Software Debugging
+24 more
Distributed Systems Python (Programming Language) Machine Learning Cloud Services Search Technologies Service Development Studio AI Infrastructure Data Logging Scripting Delivery Pipeline Large Language Models Snowflake Prompt Engineering Spring-boot Backend AI Platforms Kubernetes Machine Learning Operations Virtual Agents Restful APIs Data Pipelines Docker Databricks Microservices

Job description

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

Requirements

  • 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

About the company

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.

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