Principal, Software Engineering
Mastercard1 day ago
Dublin, IrelandStaff+
Responsibilities
- Design and build a scalable, reusable AI platform for Mastercard’s Consulting organization.
- Drive AI enablement, including agent orchestration, integration layers, AI knowledgebases, reusable skills and agents, and productivity tooling.
- Lead technical architecture and implementation with emphasis on scalability, security, performance, reliability, and enterprise standards.
- Drive migration efforts and define the future-state architecture and technology strategy.
- Collaborate with product, business, data, enterprise AI, security, compliance, sourcing, and engineering stakeholders.
- Serve as an architecture advisor for new opportunities, evaluating feasibility, risks, capabilities, and target-state designs.
- Guide architecture and platform decisions through incubation, prototyping, market testing, commercialization, and scaling.
- Identify reusable platforms, architectural patterns, capabilities, and assets across multiple opportunities.
- Mentor and influence engineers, architects, and product partners while establishing shared engineering practices and standards.
Requirements
- Bachelor’s degree in computer science or engineering, or equivalent practical experience.
- At least 8 years of full-stack engineering experience in an agile production environment.
- Significant experience building distributed, production-grade software systems.
- Experience executing technology strategy for a market-facing business with product, data science, business, and technology leaders.
- Strong understanding of GenAI, agentic workflows, AI enablement, orchestration patterns, reusable agent and skill libraries, and applied AI delivery.
- Experience scaling commercial AI, agentic, productivity, or internal platforms across large user populations.
- Strong knowledge of APIs, services, asynchronous workflows, distributed systems, and enterprise-grade software architecture.
- Experience building or integrating systems using LLMs, AI services, agent frameworks, workflow engines, or orchestration platforms.
- Strong object-oriented design, programming, and reusable component design skills.
- Familiarity with AWS EMR, Aurora, Databricks, and Snowflake for data-intensive applications.
- Strong technical judgment, communication, analysis, solution conceptualization, and stakeholder coordination skills.
- Experience working with multiple stakeholders and vendors across locations and evaluating build, buy, partner, platform, scalability, integration, and operating-model tradeoffs.
Tech Stack
DatabricksSnowflake
Categories
About Mastercard
Mastercard builds and operates a global payments network used by banks, merchants, fintechs, and governments, offering card processing, real-time payments, tokenization, and fraud/risk services. It generates revenue from transaction processing and assessment/service fees across more than 200 countries and territories. Founded in 1966 and headquartered in Purchase, New York, Mastercard is a public company listed on the NYSE (ticker: MA).