Principal Software Engineer

Mastercard Mastercard · Fintech · Dublin 18, Dublin, Ireland · Engineering

Mastercard is seeking a Principal Software Engineer to architect, build, and operate the API platform that securely exposes foundation model capabilities across the organization. This role is critical to enabling safe, scalable, and compliant adoption of generative AI and advanced analytics across Mastercard products and services.

What you'd actually do

  1. Architect and build enterprise‑grade API platforms that expose foundation model capabilities (e.g. inference, embeddings, agents) to internal consumers
  2. Define and enforce API standards, including versioning, backward compatibility, SDKs, and developer experience best practices
  3. Design and implement security and governance controls, including authentication, authorization, policy enforcement, audit logging, and usage limits
  4. Ensure platform reliability, scalability, and performance, including traffic management, caching, retries, and graceful degradation
  5. Partner with AI/ML engineering teams to productionize model capabilities while abstracting complexity from downstream consumers

Skills

Required

  • Extensive experience designing and operating large‑scale, distributed production systems
  • Deep expertise in API and platform engineering, including REST and/or gRPC, service gateways, and multi‑tenant architectures
  • Strong background in software security, including authN/authZ, encryption, secrets management, and threat modeling
  • Experience building services in cloud‑native environments (e.g. Kubernetes, managed cloud services on AWS, Azure, or GCP)
  • Proven ability to deliver reliable, observable, and cost‑efficient services in high‑availability environments
  • Strong programming skills in one or more backend languages (e.g. Java, Go, C#, Kotlin, Python)
  • Experience working in regulated or enterprise environments, with an understanding of compliance, auditability, and risk management
  • Excellent communication skills with the ability to influence technical direction across teams
  • Demonstrated leadership through technical excellence, mentorship, and architectural ownership

Nice to have

  • Familiarity with foundation model integration patterns, such as inference APIs, embeddings, RAG pipelines, and safety controls

What the JD emphasized

  • foundation model capabilities
  • generative AI
  • advanced analytics
  • production-grade APIs
  • API standards
  • security and governance controls
  • platform reliability, scalability, and performance
  • productionize model capabilities
  • observability and cost control
  • regulated or enterprise environments
  • compliance, auditability, and risk management

Other signals

  • foundation model capabilities
  • generative AI
  • advanced analytics
  • production-grade APIs
  • AI/ML engineers
  • governance
  • trust
  • inference
  • embeddings
  • agents
  • RAG pipelines
  • safety controls