Mastercard
Software Engineer II - Backend/Platform Agentic AI
Arlington, Virginia · Mid
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About the role
- 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
- Follow and contribute to engineering best practices for code quality, testing, observability, security, and reliability
Responsibilities
- 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
- Collaborate with senior engineers and platform teams to integrate PI-specific capabilities into shared AI infrastructure
Requirements
- 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
- Motivated to grow AI engineering expertise and take on increasing technical scope over time
- 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
- 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
Company info
- Build and operate services delivering AI-powered features to customers, ensuring correctness, performance, and reliability in a multi-tenant distributed environment
This listing is sourced directly from Mastercard's careers page and normalized into a canonical job model.