Senior Software Engineer - AI Platforms
About The Position
Mastercard is seeking a Senior Software Engineer to design and build production-grade AI platform capabilities that enable AI-powered products and agentic experiences across B&MI. The role focuses on reusable platform services, orchestration and runtime capabilities, and integration patterns that allow AI models, agents, tools, enterprise data, and services to operate safely and observably in customer-facing products. The engineer will partner with AI Engineers, Data Scientists, Product Managers, and platform teams. The position owns system-level concerns including identity, authorization, attribution, reliability, evaluation, guardrails, and operational controls. It is suited to engineers with distributed-systems expertise who want to apply those fundamentals to scalable, secure, production-ready AI platforms. The successful candidate will also contribute to Mastercard’s security responsibilities, including following security policies, preserving the confidentiality and integrity of accessed information, reporting suspected security violations or breaches, and completing required security training.
Requirements
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
- Proven experience building distributed, production-grade platforms, services, or software systems.
- Strong proficiency in object-oriented programming and backend development, such as Java, Kotlin, Python, or similar.
- Strong foundation in software design and architecture, data structures, and performance engineering.
- Experience designing APIs, platform services, event-driven integrations, and asynchronous workflows.
- Deep understanding of authentication, authorization, secure service-to-service communication, secure coding practices, and policy enforcement.
- Experience operating systems with high reliability, availability, observability, security, and regulatory requirements.
- Ability to work in ambiguous problem spaces, evaluate emerging AI technologies, and evolve platform capabilities iteratively.
Nice To Haves
- Experience integrating LLMs, machine learning models, or AI services into production software systems.
- Familiarity with agent frameworks, model gateways, workflow engines, orchestration platforms, retrieval patterns, or AI evaluation tooling.
- Experience designing reusable, audit-friendly, policy-driven platforms with guardrails and responsible AI controls.
Responsibilities
- Design and build scalable, resilient AI platform services and reusable capabilities for AI-powered products, intelligent workflows, and agentic systems.
- Create secure integration patterns for models, agents, tools, enterprise data, and services so actions are attributable, authorized, auditable, and observable.
- Implement orchestration and runtime patterns, including routers, supervisors, planners, stateful workflows, and asynchronous processing for multi-step AI execution.
- Build reusable frameworks for model and tool invocation, context management, error handling, retries, timeouts, and compensating actions.
- Integrate identity, permissions, policy enforcement, evaluation, and guardrails into AI execution paths.
- Ensure platform capabilities meet Mastercard standards for reliability, security, compliance, scalability, and performance, including through performance analysis and tuning.
- Drive unit, functional, and integration testing to validate platform behavior and quality.
- Collaborate with AI Engineers and Data Scientists to integrate models, prompts, and evaluation approaches into production systems.
- Own operations, including logging, monitoring, tracing, evaluation telemetry, troubleshooting, incident response, and continuous improvement.
- Review code, mentor peers, influence architectural decisions, and contribute reusable engineering standards across teams.
- Abide by Mastercard security policies and practices, protect the confidentiality and integrity of accessed information, report suspected information security violations or breaches, and complete periodic mandatory security training.
Benefits
- Medical, prescription drug, dental, vision, disability, and life insurance
- Flexible spending account and health savings account
- Paid leaves, including 16 weeks of new parent leave and up to 20 days of bereavement leave
- 80 hours of Paid Sick and Safe Time
- 25 days of vacation time and 5 personal days, prorated based on hire date
- 10 annual paid U.S. observed holidays
- 401(k) with company match
- Deferred compensation for eligible roles
- Fitness reimbursement or on-site fitness facilities
- Tuition reimbursement eligibility
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What This Job Offers
Job Type
Full-time
Career Level
Senior
