Principal AI Platform Engineer

Mastercard

Leixlip

On-site

EUR 110,000 - 150,000

Full time

6 days ago
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Job summary

Mastercard is seeking a Principal Software Engineer to accelerate consulting transformation through AI & technology. You will design a scalable AI Platform, enable agent workflows, and partner with enterprise AI, data governance, security, and engineering leaders to deliver reusable AI capabilities at scale.

This role requires strong hands-on engineering, cloud expertise, and experience shaping future-state architectures across large teams.

Qualifications

  • In-depth experience building distributed, production-grade software systems.
  • Strong OS design and object-oriented programming skills.
  • Proven ability to lead complex architectural decisions across teams.
  • Experience scaling AI-enabled platforms and reusable assets.
  • Proficient in cloud-based data and AI tooling and governance.

Responsibilities

  • Design and scale a reusable AI Platform for consulting programs.
  • Lead technical design and architecture with security and performance in mind.
  • Guide migration toward future-state architecture and standards.
  • Collaborate with product, data, and engineering leaders to align opportunities.
  • Mentor engineers and establish engineering standards and practices.
  • Partner with vendors and internal teams to deliver scalable AI solutions.

Skills

Distributed systems
Full-stack
AI platforms
Leadership
Cloud technologies
OO design
APIs & services
Architecture
Agile

Education

Bachelor’s degree in computer science or equivalent

Tools

AWS EMR
Aurora
Databricks
Snowflake

Job description

Mastercard is seeking a Principal Software Engineer to accelerate consulting transformation through AI & technology. You will design a scalable AI Platform, enable agent workflows, and partner with enterprise AI, data governance, security, and engineering leaders to deliver reusable AI capabilities at scale.

This role requires strong hands-on engineering, cloud expertise, and experience shaping future-state architectures across large teams.

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