MTS 1, Software Engineer

About the role

Global Payments and Risk builds products and platforms that enable safer, more trusted commerce experiences. We use data, modern software architectures, and AI-native engineering practices to solve risk challenges at scale across detection, decisioning, automation, and operational workflows. This team operates highly scalable systems with meaningful customer and business impact.

Responsibilities

• Design, build, test, deploy, and support production-ready AI-enabled systems that solve real customer and business problems in Risk Engineering.
• Build end-to-end services and workflows that combine LLMs, retrieval, tool use, structured outputs, deterministic logic, and human review where appropriate.
• Develop scalable backend services, APIs, and integrations that support risk decisioning, investigation, and automation use cases.
• Translate business and operational needs into clear technical designs, delivery plans, and measurable outcomes.
• Own a functional area end to end, including implementation, launch readiness, observability, monitoring, and continuous improvement.
• Define and maintain quality bars for AI behavior through task-level evaluations, offline and online metrics, regression detection, and release criteria.
• Improve reliability, scalability, latency, security, and cost efficiency of AI-enabled systems in production.
• Drive operational readiness through fallback strategies, rollback paths, incident handling, and runbooks.
• Partner with engineering, product, data science, analytics, and operations teams to deliver robust, well-governed solutions.
• Contribute high-quality code, design documents, and test plans, and raise engineering standards through thoughtful reviews and documentation.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 5+ years of software engineering experience building and operating production systems.
• Strong proficiency in the backend languages such as Java, Nodejs, TypeScript and Python.
• Experience building and shipping backend services or product features, including design, implementation, testing, launch, and production support.
• Experience building with modern AI capabilities in production or at meaningful scale, such as LLM-based workflows, tool calling, retrieval, structured outputs, workflow automation, or knowledge-grounded product experiences.
• Experience designing reliable AI-powered workflows, including prompt or context design, output validation, fallback behavior, and iterative quality improvement.
• Strong understanding of APIs, service integrations, data flows, logging, monitoring, and production debugging; familiarity with distributed systems concepts.
• Demonstrated ability to make sound engineering trade-offs across reliability, latency, scalability, cost, and developer velocity.
• Strong written and verbal communication skills, with the ability to work effectively across engineering, product, design, and other cross-functional partners.

Preferred Qualifications

• Experience building or contributing to agentic or tool-using workflows with clear guardrails and bounded autonomy.
• Experience working with evaluation workflows for AI outputs, including automated graders, benchmark tasks, error analysis, or human-in-the-loop review.
• Familiarity with search, retrieval, ranking, embeddings, or other knowledge-grounded AI patterns.
• Familiarity with secure execution practices, scoped credentials, auditability, and safe handling of AI-driven actions.
• Experience using AI to improve engineering workflows, including development, testing, debugging, or operational tooling.
• Experience instrumenting and improving systems through monitoring, experimentation, and iterative analysis of failures or regressions.
• Experience in fraud, trust, payments, risk, or other decisioning-heavy domains is a plus.
• Demonstrated ability to collaborate effectively on small technical initiatives; mentoring experience is a plus.