Mastercard

LeadSoftwareEngineer

$161–266k Arlington, Virginia, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Lead Software Engineer at Mastercard. Skills: Platform Engineering, DevOps, Software Engineering, Process Transformation. Make foundational changes to CI/CD pipelines. Improve pipeline reliability”

Industry & Context.

Problems you'll solve

Analytical thinking; Problem-solving skills

What They're Looking For.

Must Have

Extensive experience as Software Engineer, Full-stack development experience, Experience designing scalable backend services, Experience in cloud environments, Deep DevOps experience, Experience with API management, Understanding of PDLC, Experience working with large-scale data systems, Demonstrated ability to identify improvements, Experience working in Agile environments, Proven ability to lead technical initiatives, Experience mentoring engineers, Analytical thinking, Problem-solving skills, Bachelor’s degree in Computer Science, Equivalent practical experience

Nice to Have

Interest in AI-enabled engineering

What You'll Do.

Make foundational changes to CI/CD pipelines

Improve pipeline reliability

Address common use cases

Deliver market facing solutions faster

Develop reusable engineering patterns

Develop reusable frameworks

Develop reusable tools

Improve developer experience

Accelerate delivery across teams

Drive modernization of SDLC practices

Drive optimization of SDLC practices

Adopt AI intentionally

Lead AI-first engineering initiatives

Identify process improvements

Implement process improvements

Increase engineering velocity

Increase engineering quality

Increase operational efficiency

Promote best practices

Promote technical excellence

Collaborate across teams

Align technical solutions

Contribute to architectural decisions

Enable platform evolution

Support DevOps initiatives

Support platform engineering initiatives

Improve system reliability

Improve deployment efficiency

How You'll Work.

Team & Collaboration

Cross-functional teams; Platform teams; Product teams; Engineering teams

Process & Methodology

Agile

Full Job Description

**Our Purpose** _Mastercard powers economies and empowers people in 200 + countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential._ **Title and Summary** ### Lead Software Engineer ### Overview: The Accelerators group under the Business & Market Insights - Platform Engineering program at Mastercard is seeking a Lead Software Engineer to drive high-impact technical initiatives that accelerate delivery, improve platform scalability, and enable innovation across the organization. The Accelerators group is leading from the front in making meaningful contributions that allow the B&MI organization to go “faster.” This team is intentionally agile and flexible, not defined by a single technology stack, domain, or rigid process. Instead, it is composed of self-starters and self-unblockers who focus on delivering outcomes while continuously improving how those outcomes shape the next phase of platform evolution. If you're seeking an opportunity to impact a business unit across platform engineering, DevOps, software engineering, and process transformation—while also mentoring and growing others—this position is for you. This is a hybrid role based in Arlington, VA, requiring three days per week onsite. Role: • 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 • Develop reusable engineering patterns, frameworks, and tools that improve developer experience and accelerate delivery across teams. • Drive modernization and optimization of SDLC/PDLC practices through intentional AI adoption

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