Principal Software Engineer

Principal Software Engineer

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. You will design, code, prototype, and validate core platform capabilities, using modern AI‑assisted development tools to move faster, improve quality, and help teams adopt better ways of building.

• 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.
• 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.
• Apply AI tools as part of daily engineering practice to real product and platform problems.
• Teach and model adoption of AI‑assisted development, modern languages, and current engineering practices.
• Improve developer experience through automation, AI‑assisted workflows, and platform thinking.
• Advocate learnings, prototypes, and best practices across the organization.
• Own and improve end‑to‑end customer experience across a portfolio of services and applications.
• Simplify and optimize architecture strategies to balance cost, performance, and business value.
• Make trade‑offs between competing priorities and technical constraints.
• Lead architectural design for complex, enterprise‑wide initiatives spanning multiple services and programs.
• Drive organization‑wide initiatives to advance software engineering craftsmanship and best practices.
• Represent the organization through public speaking, technical blogs, and white papers on emerging technologies.
• Participate in principle‑level architecture reviews and resolve enterprise‑wide technical and regulatory challenges.
• Mentor engineers at all levels, fostering technical growth and leadership.
• Conduct technical interviews to raise the performance bar and attract top talent.
• Provide unbiased, accomplishment‑based recommendations for promotions.
• Champion AI‑assisted engineering as a default working practice and align it with organizational values.

• Excellent engineering and leadership skill with experience building high‑speed streaming platforms or distributed systems at hyperscaler‑level performance.
• AI‑native engineer – uses AI‑assisted development as default.
• Innovation leader – builds systems at massive scale and availability.
• Streaming‑first mindset – experience with low‑latency pipelines.
• Proven outcomes – delivers impactful, production‑ready systems.
• Engineering culture champion – drives best practices and transparency.
• Collaborative – works across engineering and data science teams.

• Decisioning Data & Feature Platforms: lake houses, delta lakes, distributed logs, product‑aligned data models; feature catalogs and platforms for reusable, governed features; data contracts, lineage, freshness, and quality controls.
• High‑Throughput, Low‑Latency & Real‑Time Systems: event streaming, high‑throughput data pipelines, low‑latency data technologies, real‑time transaction processing, sub‑second decisioning.
• 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 that validates 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, 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 pursuant to 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, or any other characteristic protected by law.

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