Lead Java Developer
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Job Summary
Role Overview
The 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 Responsibilities
As a Lead Software Engineer you will:
Lead hands-on architecture design and implementation of agentic applications AI-powered services and platform capabilities from concept through production
Define engineering patterns and best practices for production AI systems including evaluation monitoring guardrails resiliency cost control and rollback strategies
Drive end-to-end software delivery across the SDLC from discovery and prototyping to testing release and production operations
Use engineering tools to accelerate design coding testing documentation troubleshooting and delivery while maintaining strong engineering judgment and code quality standards
Champion an AI-enabled SDLC by improving developer workflows automation test generation code review quality release confidence and team productivity
Partner closely with Product Applied AI Data Science and business stakeholders to translate ambiguous opportunities into scalable product capabilities
Provide technical leadership through architectural decisions design reviews code reviews hands-on contribution and mentoring of engineers across the team
Build highly available secure and maintainable cloud-native services with strong observability performance and operational readiness
Shape technical roadmaps identify short- and long-term platform needs and influence architecture choices that enable scale reuse and faster delivery
Collaborate across teams and business units to solve complex business and engineering problems with practical high-impact solution
Keep senior stakeholders informed of progress risks trade-offs and implementation decisions in a clear and concise manner
Requirements
Ideal Candidate Qualifications:
Strong software engineering experience building scalable secure maintainable production systems including experience leading complex technical initiatives end to end
Hands-on experience building and shipping AI-powered products or agentic applications using LLMs orchestration frameworks tool-calling patterns retrieval and context-aware workflows
Strong understanding of agentic system design including planning reasoning loops workflow orchestration memory grounding evaluation safety and human-in-the-loop controls
Experience taking AI solutions from prototype to production with sound engineering discipline around reliability observability latency cost security and governance
Experience with modern AI frameworks SDKs and tooling for building AI applications agent workflows and developer productivity use cases
Strong programming skills in one or more backend languages such as Java and Python with the ability to write high-quality well-tested production-ready code
Experience with modern front-end frameworks such as React and/or for building intuitive product experiences would be beneficial
Experience building services in cloud-native environments using Kubernetes and managed cloud services on AWS Azure
Good understanding of APIs distributed systems event-driven architectures data pipelines and integration patterns across enterprise platforms
Experience with CI/CD automated testing and engineering automation including the ability to improve SDLC efficiency and release quality using AI tools
Practical experience using AI coding and engineering assistants to improve productivity across design implementation testing debugging documentation and operational support
Strong background in software security including authentication authorisation secrets management encryption threat modelling and secure deployment practices for AI-enabled systems
Proven ability to create reusable platforms frameworks or internal engineering capabilities that improve developer experience and accelerate delivery across teams
Strong product mindset with the ability to translate user needs and business goals into practical high-impact technical solutions
Excellent collaboration and communication skills with experience influencing across engineering product data science and leadership stakeholders
Skills Matrix
Bucket | Skills / Metrics |
Must-Have | Strong hands-on programming expertise in Java and Python with the ability to design build test and optimise production-grade backend services Strong experience with React for building modern responsive and intuitive user interfaces for enterprise applications Experience with or modern front-end architecture patterns alongside React Deep experience building cloud-native applications using containers Kubernetes microservices and managed cloud services in AWS and/or Azure Strong expertise in designing and building APIs including RESTful services service contracts versioning security and integration patterns Proven experience with event-driven architecture asynchronous messaging streaming and resilient distributed system design Practical experience using AI tools to improve engineering productivity across coding testing debugging documentation and release workflows Strong understanding of software engineering quality metrics such as code quality test automation reliability performance observability and maintainability |
Good to Have | Experience building agentic applications or AI-powered systems using LLMs orchestration frameworks retrieval tool calling and workflow automation Experience with API gateway service mesh and enterprise integration patterns Experience with Kafka event streaming platforms or large-scale messaging ecosystems Exposure to CI/CD automation infrastructure as code and release engineering practices Experience in regulated enterprise environments where security governance compliance and auditability are critical Ability to mentor engineers and influence architecture engineering standards and developer productivity at team level |
All About You
You 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
Required Skills:
Understanding of event-driven architectures Distributed systems - How clusters are formed Quorum management Failure handling. 3 to 5 years of hands-on Experience in MQ or NATS broker or similar messaging solutions. Understanding of Kafka clustering would be good to have. Knows Client-Server communication aspects - sockets TLS protocol etc Understands the concept of region and AZs. Provide L2 support production systems like application database middleware components infrastructure and network components. Manage production incidents end-to-end within defined SLAs with focus on resolution rather than who caused it. Interact with various stakeholders such as Release managers program leads service managers development and test leads Review operational readiness requirements such as monitoring and alerting log rotation and resilience of the components and report the gaps Provide pre-implementation support with activities such as release notes review and implementation dry runs. Protect production components by running health checks monitoring latency and memory utilization. Automate day-to-day activities and propose changes that improve reliability Participate in CAB and provide feedback on change requests Support the DevOps team in testing the promoted pipelines and suggest automation of configuration items. Practice incident management best practices and perform RCA. Participate in disaster recovery tests and operational acceptance tests Analyze the technology stack that makes up the product and optimize recovery time objective. Work with team members spread across and time zones Share knowledge document improvements and mentor junior resources It is good to have skills using Jenkins to orchestrate builds and link to Sonar Maven etc. to build out the CI/CD pipeline. Support deployments of code into multiple lower environments. Supporting current processes needed with an emphasis on automating everything as soon as possible. It is good to have skill to design Implement and enhance our deployment automation based on Chef. We need proven experience designing and implementing an overall release and deployment process. It is good to have skill to design and implement a Git based code management strategy that will support multiple environment deployments in parallel. Experience with automation for Branch management code promotions and version management. Engage in and improve the whole lifecycle of servicesfrom inception and design through deployment operation and refinement. Requirements MQ/EB Understanding of event-driven architectures Distributed systems - How clusters are formed Quorum management Failure handling. 3 to 5 years of hands-on Experience in MQ or NATS broker or similar messaging solutions. An understanding of Kafka clustering would be good to have. Knows Client-Server communication aspects - sockets TLS protocol etc Understand the concept of region and AZs. Deployments MTF/Prod Maintenance items (including stop/start Disaster Recovery-related activities etc.) CR for changes in MTF/Prod Good knowledge on Nginx Tools - Log Monitoring Tool - Splunk Application Monitoring tool - Dynatrace Ticketing incident/problem management tool - Remedy Dev-ops Basics - CI-CD Basics Overview of Git Bit-bucket SonarQube Ansible/Chef Skills - Linux & Shell Scripting ITIL / ITSM PL/SQL Troubleshooting Jenkins - CI/CD Groovy Scripting/Yaml Ansible/Chef Nginx Java / JEE Event-Driven Architectures MQ or NATS broker or similar messaging solutions. Kafka Client-server communication aspects - sockets TLS protocol Understand the concept of region and AZs.
