Principal AI Platform Engineer - Scale & Enable AI

Mastercard

Donabate

On-site

EUR 120,000 - 180,000

Full time

6 days ago
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Job summary

Mastercard, a global payments technology company, seeks a Principal Engineer in the Advisors & Transformation group to accelerate consulting transformation with AI and technology. You will design a scalable AI Platform, drive AI productivity across the organization, and support AI-enabled opportunities with product, data, and engineering partners.

The role requires leadership across multiple teams, governance of security and reliability, and hands-on engineering excellence in a large, enterprise

Qualifications

  • Bachelor’s degree in computer science, Engineering, or equivalent practical experience.
  • Significant professional experience building distributed, production-grade software systems in an agile environment (8+ years).
  • Experience executing a technology strategy for a market-facing business with cross-functional partners.
  • Strong understanding of GenAI, agentic workflows, AI enablement, orchestration patterns, and enterprise AI delivery.

Responsibilities

  • Design and build a scalable, reusable AI Platform for the program.
  • Lead technical design and architecture, ensuring scalability, security, and performance.
  • Drive migration to future state architecture and collaborate with cross-functional teams to deliver AI solutions.
  • Mentor engineering teams and influence engineering standards and decisions.

Skills

GenAI
Agentic workflows
APIs & services
Distributed systems
OO design
Agile

Education

Bachelor's degree in CS/Engineering

Tools

AWS EMR
Aurora
Databricks
Snowflake

Job description

Mastercard, a global payments technology company, seeks a Principal Engineer in the Advisors & Transformation group to accelerate consulting transformation with AI and technology. You will design a scalable AI Platform, drive AI productivity across the organization, and support AI-enabled opportunities with product, data, and engineering partners.

The role requires leadership across multiple teams, governance of security and reliability, and hands-on engineering excellence in a large, enterprise

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