Principal Software Engineer

Title and Summary

Principal Software Engineer

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

As a Principal Engineer within the Decision Stream program, you will combine enterprise-scale technical leadership with hands‑on engineering for the next‑generation Decision Management Platform. This role requires active design, coding, prototyping, and validation of core platform capabilities using modern AI‑assisted development tools to improve quality, speed, and adoption of better engineering practices.

• Platform & Product Development:
  Build software, tooling, and platform capabilities.
• Design and implement large‑scale distributed systems.
• Develop reusable services, patterns, and integrations.
• Contribute to new product and prototype development from concept through validation.
• Evaluation & Technical Judgment:
  Evaluate systems, frameworks, and tools across quality, cost, latency, scalability, reliability, and maintainability.
• Apply sound engineering judgment to trade‑offs in distributed systems design and architecture.
• Developer Experience & Enablement:
  Apply AI tools in daily engineering, teach adoption, improve developer experience through automation and AI workflows, and advocate best practices.
• Customer Experience & Platform Strategy:
  Own and improve end‑to‑end customer experience; simplify and optimize architecture strategies; make trade‑offs between competing priorities and technical constraints.
• Thought Leadership & Influence:
  Lead architectural design for complex initiatives, drive organization‑wide engineering initiatives, represent the organization through public speaking, technical blogs, and white papers, participate in principle‑level architecture reviews.
• Talent & Culture:
  Mentor engineers, conduct technical interviews, provide unbiased promotion recommendations, champion AI‑assisted engineering, and align with organizational values.

• AI‑native engineer who uses AI‑assisted development as default.
• Innovation leader who builds systems at massive scale and availability.
• Streaming‑first mindset with experience in low‑latency pipelines.
• Proven outcomes delivering impactful, production‑ready systems.
• Engineering culture champion driving best practices and transparency.
• Collaborative, working across engineering and data science teams.

Candidates do not need to be experts in all areas, but should demonstrate hands‑on depth and expertise in one or more of the following:

• Decisioning Data & Feature Platforms: lake houses, delta lakes, distributed logs, product‑aligned data models; feature catalogs, engineering platforms; data contracts, lineage, freshness controls.
• High‑Throughput, Low‑Latency & Real‑Time Systems:
  Event streaming, high‑throughput data pipelines; low‑latency data technologies; real‑time transaction processing.
• AI & ML Systems: ML lifecycle engineering, agentic AI patterns, LLM integration, prompt engineering; model observability, drift detection, feedback loops.
• Decisioning Tooling & UX:
  Authoring, testing, deployment of business rules engine rules; tooling to validate rules, models, and policies pre‑deployment; operator experience for authors, analysts, and SREs.
• Cloud Infrastructure, Platform Engineering & Dev Ops: AWS infrastructure engineering, cloud‑native platform patterns, Dev Ops automation, CI/CD, observability, Git Ops.

• Extensive experience in software engineering and technical leadership.
• Proven delivery of large‑scale distributed systems.
• Expertise in cloud, AI/data platforms, and modern engineering practices.
• Strong communication and mentorship skills.
• Bachelor’s degree (or equivalent); advanced degree preferred.
• Telecommuting and/or working from home may be permissible per company policies.

Mastercard is a merit‑based, inclusive, equal‑opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability, or veteran status. In the US or Canada, if you require accommodations, please contact reasonable

• Abide by Mastercard’s security policies and practices.
• Ensure the confidentiality and integrity of information accessed.
• Report any suspected information security violations or breaches.
• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

O'Fallon, Missouri: $170,000 - $281,000 USD