Senior Software Engineer

Mastercard Mastercard · Fintech · O Fallon, MO +1 · Engineering

The Senior Software Engineer will work on the AI & DPE organization's DMP platform, a cloud-native, real-time decisioning and AI inferencing system for fraud detection and enterprise decision management. The role involves hands-on rule authoring, platform modernization, and implementing best practices for high-throughput, low-latency systems, with a focus on AI technologies like Gen AI and LLMs within the fraud domain.

What you'd actually do

  1. Proven experience in the modernization of platforms related to Fraud Rules/Engines and large-scale migrations.
  2. Build and operate scalable global platforms with high throughput, low latency, and 5 9’s availability.
  3. Serve as a hands-on Rule Author with deep experience in Fraud Rules Engines.
  4. Apply familiarity with AI technologies like Gen AI and LLMs relevant to Fraud Rules.
  5. Follow solution architectural designs and ensure alignment with business needs, infrastructure capabilities, and security and compliance requirements.

Skills

Required

  • Software development
  • Fraud Rule Engines
  • large-scale migrations
  • Java
  • Python
  • Go
  • DevOps
  • IT Operations
  • declarative paradigms
  • functional programming
  • relational databases
  • NoSQL databases
  • performance tuning
  • automation
  • Financial Domain experience
  • Banking Domain
  • AI technologies
  • Gen AI
  • LLMs

Nice to have

  • familiarity with AI technologies like Gen AI and LLMs relevant to Fraud Rules
  • understanding of loosely coupled and stateless systems
  • performance tuning
  • automation

What the JD emphasized

  • high throughput, low latency
  • 5 9’s availability
  • Fraud Rules Engines
  • AI technologies like Gen AI and LLMs
  • security and compliance requirements
  • writing rules
  • rule quality
  • Java, Python, or Go
  • automation
  • DevOps and IT Operations best practices
  • large-scale migrations
  • declarative paradigms and functional programming
  • relational and NoSQL databases
  • loosely coupled and stateless systems
  • performance tuning
  • Financial Domain experience
  • Banking Domain

Other signals

  • AI inferencing system
  • modernizing Fraud Rule Engines and integrating advanced AI capabilities
  • AI technologies like Gen AI and LLMs relevant to Fraud Rules
  • Demonstrated track record with AI