Lead the architecture, development, and productionization of AI-powered products, intelligent agents, and cloud-native analytics platforms. Design agentic systems with reasoning, memory, retrieval, evaluation, safety, and human oversight. Build scalable services and APIs using AWS, Azure, Databricks, Spark, Python, and Java. Drive technical execution, architecture reviews, DevSecOps, testing, reliability, governance, and cost optimization while mentoring engineers and coordinating globally distributed teams.
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
Who is Mastercard?
Mastercard is the global technology company behind the world's fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, and a technology innovation lab. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you.
Position Responsibilities:
At Mastercard Services, you will serve as a senior technical leader and hands-on engineer for BE&O's next-generation experimentation and analytics platform. As a Lead Software Engineer, you will lead through technical influence, architectural judgment, and execution excellence to help modernize our platform and deliver scalable, secure, cloud-native capabilities for global business users.
Design, develop, and deploy AI-powered products, intelligent agents, and agentic workflows utilizing Large Language Models (LLMs), retrieval systems, orchestration frameworks, tool-calling patterns, and context-aware workflows.
Architect and implement advanced agentic systems incorporating planning, reasoning loops, memory management, grounding, evaluation frameworks, safety mechanisms, and human-in-the-loop controls.
Lead the transition of AI solutions from proof-of-concept to production by establishing best practices for reliability, observability, performance, security, governance, and cost optimization.
Develop scalable AI applications and developer productivity solutions using modern AI frameworks, SDKs, and orchestration platforms.
Serve as a hands-on technical contributor, designing, coding, testing, debugging, and delivering production-quality software across the full engineering lifecycle.
Build and evolve scalable services, APIs, and analytical capabilities using modern engineering practices, cloud platforms, and data technologies such as AWS, Azure, Databricks, Spark/PySpark, Python, Java and related frameworks.
Partner closely with product managers, engineering teams, architects, data scientists, QA, security, and operations teams to translate business and functional requirements into robust technical solutions.
Coordinate and lead technical execution across globally distributed engineering teams, ensuring alignment across regions, time zones, dependencies, design decisions, and delivery milestones.
Drive architecture and design reviews, code reviews, technical decision-making, and engineering tradeoff discussions to ensure solutions are secure, resilient, observable, performant, maintainable, and aligned with enterprise standards.
Drive engineering excellence through CI/CD automation, DevSecOps practices, automated testing, and AI-assisted software development workflows.
Establish reusable platforms, frameworks, accelerators, and engineering capabilities that improve developer productivity and accelerate solution delivery across teams.
Identify opportunities to improve platform scalability, reliability, developer productivity, operational readiness, and speed of delivery through modernization, automation, reusable patterns, and engineering best practices.
Provide technical mentorship to junior and mid-level engineers through design guidance, code review, pairing, knowledge sharing, and modeling strong engineering judgment.
Navigate ambiguity in complex initiatives by clarifying technical direction, decomposing large problems, identifying risks, and driving alignment across stakeholders.
Champion a culture of engineering excellence, continuous improvement, ownership, collaboration, and high-quality delivery across the team and partner organizations.
Ideal Candidate Qualifications:
8+ years of software engineering experience delivering scalable, high-performance, and reliable software in an agile environment.
Strong hands-on experience designing and building distributed systems, microservices, RESTful APIs, and cloud-native applications.
Strong experience with data-intensive applications and analytics platforms; experience with Databricks, Spark, or PySpark is highly desirable.
Proven experience building and delivering AI-powered applications, intelligent agents, or generative AI solutions in enterprise environments.
Strong understanding of agentic AI architectures, including workflow orchestration, reasoning frameworks, memory systems, grounding techniques, evaluation methodologies, and safety controls.
Hands-on experience with modern AI frameworks, SDKs, orchestration platforms, vector databases, retrieval systems, and agent development tooling.
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
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
Who is Mastercard?
Mastercard is the global technology company behind the world's fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, and a technology innovation lab. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you.
Position Responsibilities:
At Mastercard Services, you will serve as a senior technical leader and hands-on engineer for BE&O's next-generation experimentation and analytics platform. As a Lead Software Engineer, you will lead through technical influence, architectural judgment, and execution excellence to help modernize our platform and deliver scalable, secure, cloud-native capabilities for global business users.
Design, develop, and deploy AI-powered products, intelligent agents, and agentic workflows utilizing Large Language Models (LLMs), retrieval systems, orchestration frameworks, tool-calling patterns, and context-aware workflows.
Architect and implement advanced agentic systems incorporating planning, reasoning loops, memory management, grounding, evaluation frameworks, safety mechanisms, and human-in-the-loop controls.
Lead the transition of AI solutions from proof-of-concept to production by establishing best practices for reliability, observability, performance, security, governance, and cost optimization.
Develop scalable AI applications and developer productivity solutions using modern AI frameworks, SDKs, and orchestration platforms.
Serve as a hands-on technical contributor, designing, coding, testing, debugging, and delivering production-quality software across the full engineering lifecycle.
Build and evolve scalable services, APIs, and analytical capabilities using modern engineering practices, cloud platforms, and data technologies such as AWS, Azure, Databricks, Spark/PySpark, Python, Java and related frameworks.
Partner closely with product managers, engineering teams, architects, data scientists, QA, security, and operations teams to translate business and functional requirements into robust technical solutions.
Coordinate and lead technical execution across globally distributed engineering teams, ensuring alignment across regions, time zones, dependencies, design decisions, and delivery milestones.
Drive architecture and design reviews, code reviews, technical decision-making, and engineering tradeoff discussions to ensure solutions are secure, resilient, observable, performant, maintainable, and aligned with enterprise standards.
Drive engineering excellence through CI/CD automation, DevSecOps practices, automated testing, and AI-assisted software development workflows.
Establish reusable platforms, frameworks, accelerators, and engineering capabilities that improve developer productivity and accelerate solution delivery across teams.
Identify opportunities to improve platform scalability, reliability, developer productivity, operational readiness, and speed of delivery through modernization, automation, reusable patterns, and engineering best practices.
Provide technical mentorship to junior and mid-level engineers through design guidance, code review, pairing, knowledge sharing, and modeling strong engineering judgment.
Navigate ambiguity in complex initiatives by clarifying technical direction, decomposing large problems, identifying risks, and driving alignment across stakeholders.
Champion a culture of engineering excellence, continuous improvement, ownership, collaboration, and high-quality delivery across the team and partner organizations.
Ideal Candidate Qualifications:
8+ years of software engineering experience delivering scalable, high-performance, and reliable software in an agile environment.
Strong hands-on experience designing and building distributed systems, microservices, RESTful APIs, and cloud-native applications.
Strong experience with data-intensive applications and analytics platforms; experience with Databricks, Spark, or PySpark is highly desirable.
Proven experience building and delivering AI-powered applications, intelligent agents, or generative AI solutions in enterprise environments.
Strong understanding of agentic AI architectures, including workflow orchestration, reasoning frameworks, memory systems, grounding techniques, evaluation methodologies, and safety controls.
Hands-on experience with modern AI frameworks, SDKs, orchestration platforms, vector databases, retrieval systems, and agent development tooling.
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
- Abide by Mastercard's security policies and practices;
- Ensure the confidentiality and integrity of the information being accessed;
- Report any suspected information security violation or breach, and
- Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.
Mastercard Dublin, Dublin, IRL Office
One South County, South County Business Park, Dublin, Dublin, Ireland, D18
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