Lead, Software Engineer
Mastercard3 days ago
Dublin, IrelandStaff+
Responsibilities
- Lead hands-on development of AI and agentic systems and scalable, reusable AI platform capabilities.
- Integrate LLMs, AI services, agent frameworks, workflow engines, knowledge bases, orchestration platforms, and related services.
- Design and deliver APIs, services, event-driven workflows, data pipelines, agent workflows, and user-facing platform capabilities.
- Translate target-state architecture and product priorities into technical designs, delivery plans, and working solutions.
- Provide technical direction to junior engineers and vendor teams, including design reviews, code reviews, mentoring, and production-readiness oversight.
- Support migration toward future-state architecture while maintaining operational continuity.
- Help scale Claude, Copilot, and Cowork and make reusable AI patterns, skills, and agents easier to adopt.
- Identify technical risks, evaluate build-versus-buy and reuse trade-offs, and ensure alignment with security, privacy, compliance, reliability, and scale expectations.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
- Strong hands-on AI engineering experience and experience with large-scale data platforms and modern ML/AI tooling.
- Experience building or integrating LLM, AI service, agent framework, workflow engine, orchestration, vector search, retrieval-augmented generation, or related solutions.
- Understanding of generative AI and agentic workflows, including prompt design, grounding, tool use, evaluation, guardrails, monitoring, and responsible AI.
- Familiarity with AWS EMR, Aurora, Databricks, Snowflake, or comparable data-intensive cloud platforms.
- Strong software engineering, system design, distributed systems, object-oriented design, and programming skills.
- Professional experience building and operating distributed, production-grade software, including substantial full-stack or backend engineering experience.
- Experience leading technical delivery for a team or workstream, including planning, design reviews, code reviews, mentoring, and production readiness.
- Ability to influence technical direction without formal people-management responsibility and evaluate architecture, security, scalability, integration, cost, delivery, and operational trade-offs.
- Strong written and verbal communication skills and ability to coordinate across teams, locations, vendors, and business stakeholders.
- Previous experience building an AI platform in an advisory or consultancy environment is a distinct advantage.
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).