Principal AI Platform Engineer

Mastercard

Howth

On-site

EUR 120,000 - 180,000

Full time

6 days ago
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Job summary

Mastercard is seeking a Principal Engineer to accelerate its AI-enabled consulting transformation. You will design a scalable AI Platform, drive AI productivity across the organization, and lead architecture decisions with product, data, and engineering leaders.

The role requires hands-on technologist with strong OO design and cloud experience. You will mentor engineers, shape reusable capabilities, and ensure solutions meet security, reliability, and scale standards while collaborating with

Qualifications

  • Bachelor’s degree in CS, Engineering, or equivalent practical experience.
  • 8+ years of full-stack engineering in an agile environment.
  • Experience building production-grade distributed software systems.
  • Strong knowledge of GenAI, agentic workflows, and AI delivery at scale.
  • Cloud technologies and platforms like AWS, Databricks, Snowflake.

Responsibilities

  • Design and build scalable AI Platform for program.
  • Drive AI enablement across the wider group.
  • Lead architecture, ensuring security, scalability, and performance.
  • Own migration and evolution toward future state architecture.
  • Collaborate with product, data, and engineering teams to deliver AI solutions.

Skills

Distributed systems
Full-stack engineering
AI/ML platforms
Cloud architecture
APIs & services
Leadership & mentoring
Agile / cross-functional collaboration

Education

Bachelor’s degree in computer science or related

Tools

AWS
Databricks
Snowflake

Job description

Mastercard is seeking a Principal Engineer to accelerate its AI-enabled consulting transformation. You will design a scalable AI Platform, drive AI productivity across the organization, and lead architecture decisions with product, data, and engineering leaders.

The role requires hands-on technologist with strong OO design and cloud experience. You will mentor engineers, shape reusable capabilities, and ensure solutions meet security, reliability, and scale standards while collaborating with

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