Role OverviewThe team is looking for a Lead Software Engineer to help build the next generation of intelligent, agentic products and platforms powering the Mastercard Virtual C‐Suite.
This is a hands‐on technical leadership role for an experienced engineer who combines strong software engineering fundamentals with practical experience building production‐ready AI systems.
You will lead the design and delivery of secure, scalable, and reliable agentic applications that can reason, orchestrate tools, interact with enterprise systems, and deliver measurable business value.
You will work closely with Applied AI, Data Science, Product, Security, and Platform teams to move from concept to experimentation to governed production deployment.
This role will suit a builder who enjoys solving complex problems, working across disciplines, and helping teams deliver high‐quality software at pace.
We are particularly interested in engineers who know how to use AI responsibly both within products and across the software development lifecycle to improve quality, productivity, engineering effectiveness, and delivery outcomes.
Based in Ireland, this role offers the opportunity to work on globally scaled products while collaborating with distributed teams across regions.
We welcome candidates from a range of backgrounds and experiences who are excited by the opportunity to shape practical AI innovation in a regulated, high‐impact environment.Position ResponsibilitiesLead hands‐on architecture, design, and implementation of agentic applications, AI‐powered services, and platform capabilities from concept through productionDefine engineering patterns and best practices for production AI systems, including evaluation, monitoring, guardrails, resiliency, cost control, and rollback strategiesDrive end‐to‐end software delivery across the SDLC, from discovery and prototyping to testing, release, and production operationsUse engineering tools to accelerate design, coding, testing, documentation, troubleshooting, and delivery while maintaining strong engineering judgment and code quality standardsChampion an AI‐enabled SDLC by improving developer workflows, automation, test generation, code review quality, release confidence, and team productivityPartner closely with Product, Applied AI, Data Science, and business stakeholders to translate ambiguous opportunities into scalable product capabilitiesProvide technical leadership through architectural decisions, design reviews, code reviews, hands‐on contribution, and mentoring of engineers across the teamBuild highly available, secure, and maintainable cloud‐native services with strong observability, performance, and operational readinessShape technical roadmaps, identify short‐ and long‐term platform needs, and influence architecture choices that enable scale, reuse, and faster deliveryCollaborate across teams and business units to solve complex business and engineering problems with practical, high‐impact solutionKeep senior stakeholders informed of progress, risks, trade‐offs, and implementation decisions in a clear and concise mannerRequirementsStrong software engineering experience building scalable, secure, maintainable production systems, including experience leading complex technical initiatives end to endHands‐on experience building and shipping AI‐powered products or agentic applications using LLMs, orchestration frameworks, tool‐calling patterns, retrieval, and context‐aware workflowsStrong understanding of agentic system design, including planning, reasoning loops, workflow orchestration, memory, grounding, evaluation, safety, and human‐in‐the‐loop controlsExperience taking AI solutions from prototype to production with sound engineering discipline around reliability, observability, latency, cost, security, and governanceExperience with modern AI frameworks, SDKs, and tooling for building AI applications, agent workflows, and developer productivity use casesStrong programming skills in one or more backend languages such as Java and Python, with the ability to write high‐quality, well‐tested, production‐ready codeExperience with modern front‐end frameworks such as React and/or Next.Js for building intuitive product experiences would be beneficialExperience building services in cloud‐native environments using Kubernetes and managed cloud services on AWS, AzureGood understanding of APIs, distributed systems, event‐driven architectures, data pipelines, and integration patterns across enterprise platformsExperience with CI/CD, automated testing, and engineering automation, including the ability to improve SDLC efficiency and release quality using AI toolsPractical experience using AI coding and engineering assistants to improve productivity across design, implementation, testing, debugging, documentation, and operational supportStrong background in software security, including authentication, authorisation, secrets management, encryption, threat modelling, and secure deployment practices for AI‐enabled systemsProven ability to create reusable platforms, frameworks, or internal engineering capabilities that improve developer experience and accelerate delivery across teamsStrong product mindset with the ability to translate user needs and business goals into practical, high‐impact technical solutionsExcellent collaboration and communication skills, with experience influencing across engineering, product, data science, and leadership stakeholdersSkills MatrixMust‐HaveStrong hands‐on programming expertise in Java and Python, with the ability to design, build, test, and optimise production‐grade backend servicesStrong experience with React for building modern, responsive, and intuitive user interfaces for enterprise applicationsExperience with Next.Js or modern front‐end architecture patterns alongside ReactDeep experience building cloud‐native applications using containers, Kubernetes, microservices, and managed cloud services in AWS and/or AzureStrong expertise in designing and building APIs, including RESTful services, service contracts, versioning, security, and integration patternsProven experience with event‐driven architecture, asynchronous messaging, streaming, and resilient distributed system designPractical experience using AI tools to improve engineering productivity across coding, testing, debugging, documentation, and release workflowsStrong understanding of software engineering quality metrics such as code quality, test automation, reliability, performance, observability, and maintainabilityGood to HaveExperience building agentic applications or AI‐powered systems using LLMs, orchestration frameworks, retrieval, tool calling, and workflow automationExperience with API gateway, service mesh, and enterprise integration patternsExperience with Kafka, event streaming platforms, or large‐scale messaging ecosystemsExposure to CI/CD automation, infrastructure as code, and release engineering practicesExperience in regulated enterprise environments where security, governance, compliance, and auditability are criticalAbility to mentor engineers and influence architecture, engineering standards, and developer productivity at team levelAll About YouYou are a hands‐on technical leader who enjoys building and shipping real products, not just prototypes.
You have experience building or operating AI‐enabled or agentic applications in production and understand what it takes to make them secure, reliable, and useful at scale.
You combine strong software engineering fundamentals with curiosity and good judgment in applying emerging AI capabilities to real business problems.
You actively use AI to enhance your own engineering productivity and help teams adopt better ways of designing, coding, testing, documenting, and operating software.
You understand where AI can accelerate delivery and where human review, engineering discipline, and thoughtful controls remain essential.
You care deeply about customer value, developer experience, quality, resilience, and long‐term maintainability.
You are comfortable working in collaborative, cross‐functional, and internationally distributed teams.
You raise the bar for others through mentorship, technical leadership, and a practical, delivery‐focused mindset.
You communicate complex technical concepts clearly and effectively to both engineering teams and senior stakeholders.
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