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About the Role

Lead enterprise-scale technical initiatives and hands-on engineering for the next-generation Decision Management Platform. Design, code, prototype, and validate core platform capabilities using modern AI-assisted development tools. Focus on leveraging real-time AI inferencing and decisioning to enhance product effectiveness, business delivery, technical resilience, and lower cost of ownership. Collaborate with technology executives, senior leaders, and engineers to shape the overall AI & DPE technology strategy.

Responsibilities

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 the 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.
Apply judgment and experience to 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.

Requirements

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.
Ability to thrive on solving complex engineering challenges at scale.
Experience building high-speed streaming platforms or distributed systems at hyperscaler-level performance.
Proficiency in AI-assisted development.
Experience building systems at massive scale and availability.
Streaming-first mindset with experience in low-latency pipelines.
Track record of delivering impactful, production-ready systems.
Champion of engineering best practices and transparency.
Collaborative approach, working effectively across engineering and data science teams.

Skills

Data architectures for decisioning: lakehouses, delta lakes, distributed logs, product-aligned data models.
Feature catalogs and engineering platforms for reusable, governed features.
Decisioning data models covering events, derived features, reference data, labels, outcomes, and policy data.
Data contracts, lineage, freshness, and quality controls for decisioning data.
Event streaming and high-throughput data pipelines.
Low-latency data technologies: distributed caches, in-memory data grids.
Real-time transaction processing and sub-second decisioning.
ML lifecycle engineering: model training, deployment, refresh, low-latency inference.
Agentic AI patterns, LLM integration, and prompt engineering.
Model observability, drift detection, and feedback loops for AI systems.
Authoring, testing, and deployment of business rules engine rules and decisioning logic.
Tooling for validating rules, models, and policies pre-deployment.
Operator experience for authors, analysts, and SREs: lifecycle, approvals, observability, and explainability of live decisions.
Rules engine design and modernization.
AWS infrastructure engineering and cloud-native platform patterns.
DevOps and platform engineering: automation, CI/CD, observability, GitOps.

Location

O'Fallon, Missouri
Remote option available

Work Type

Full-time
Remote option

Experience Level

Principal Engineer
Extensive experience in software engineering and technical leadership

Education Level

Bachelor’s degree (or equivalent)
Advanced degree preferred

Salary/Compensations

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

Benefits

Medical insurance
Prescription drug insurance
Dental insurance
Vision insurance
Disability insurance
Life insurance
Flexible spending account
Health savings account
16 weeks of new parent leave
Up to 20 days of bereavement leave
80 hours of Paid Sick and Safe Time
25 days of vacation time (pro-rated based on date of hire)
5 personal days (pro-rated based on date of hire)
10 annual paid U.S. observed holidays
401k with a best-in-class company match
Deferred compensation for eligible roles
Fitness reimbursement or on-site fitness facilities
Eligibility for tuition reimbursement

About the Company

Mastercard is a global technology company in the payments industry.
Powers economies and empowers people in over 200 countries and territories.
Mission to connect and power an inclusive, digital economy, making transactions safe, simple, smart, and accessible.
Utilizes secure data, networks, partnerships, and innovation to help individuals, financial institutions, governments, and businesses realize their potential.
Committed to building a sustainable world that unlocks priceless possibilities for all.
Innovates solutions for easier payments, faster checkouts, increased merchant sales, financial access, simplified corporate purchasing, efficient commuting, government efficiencies, global access for small businesses, and fraud prevention for retailers.

Equal Opportunity

Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.
We hire the most qualified candidate for the role.
In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.