Lead Software Engineer

Mastercard Mastercard · Fintech · Arlington, VA +1 · Engineering

Lead Software Engineer for the Accelerators group, focusing on CI/CD, platform scalability, and developer experience. Drives modernization through AI adoption and AI-first engineering initiatives, mentors engineers, and contributes to architectural decisions. Requires strong full-stack, cloud, and DevOps experience.

What you'd actually do

  1. Make foundational changes to the CI/CD pipelines and practices at Mastercard to improve reliability, address common use cases, and deliver market facing solutions faster
  2. Develop reusable engineering patterns, frameworks, and tools that improve developer experience and accelerate delivery across teams.
  3. Drive modernization and optimization of SDLC/PDLC practices through intentional AI adoption and AI-first engineering initiatives.
  4. Identify and implement process improvements that increase engineering velocity, quality, and operational efficiency.
  5. Mentor and guide engineers across Mastercard’s engineering community, promoting best practices and technical excellence.

Skills

Required

  • Extensive experience as a Software Engineer, Full-Stack Engineer, or Platform Engineer
  • Strong full-stack development experience across modern stacks (.NET, Java, React, JavaScript, SQL Server, PostgreSQL, or similar)
  • Proven experience designing and building scalable backend services, APIs, and distributed systems
  • Strong experience in cloud environments (AWS and/or Azure)
  • Deep DevOps and platform engineering experience, including CI/CD pipelines (Jenkins, GitHub Actions) and deployment automation
  • Experience with API management, gateway technologies, secrets management, and infrastructure tooling
  • Strong understanding of Product Development Life Cycle (PDLC)
  • Experience working with large-scale data systems, including ETL pipelines and high-volume data processing environments
  • Demonstrated ability to identify and implement engineering efficiency improvements
  • Strong interest in AI-enabled engineering
  • Experience working in Agile environments
  • Proven ability to lead technical initiatives
  • Experience mentoring or coaching engineers
  • Strong analytical thinking, problem-solving skills
  • Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience

What the JD emphasized

  • AI adoption
  • AI-first engineering