Senior Java Software Engineer

Role: Sr. Java Software Engineer

Location: Nenagh, Ireland

Type: Contract

Job Description

• Design, build, and deliver high-quality microservices and event-driven capabilities that support modern digital experiences.
• Partner with architecture, product, data, and AI teams to integrate machine learning and AI-assisted workflows into customer and operational journeys.
• Lead the decomposition and modernization of legacy systems using domain-driven design, strangler patterns, and AI-assisted refactoring techniques.
• Design, instrument, and document systems so AI copilots and automated runbooks can safely observe, learn, and act through robust telemetry, feature flags, and guardrails.
• Drive engineering excellence through effective design reviews, automated testing, resilience and chaos engineering practices, and well-defined reliability standards.
• Improve developer experience through automated CI/CD pipelines, infrastructure-as-code, policy-as-code, and AI-enabled engineering tools that shorten feedback loops.
• Coach and mentor engineers in AI-first ways of working, including effective use of copilots, prompt literacy, responsible AI practices, and disciplined experimentation.
• Balance innovation and transformation with delivery commitments by making pragmatic, data-informed engineering decisions and communicating risks proactively.

What You’ll Need

• Proven experience delivering software in complex, distributed, and highly regulated environments.
• Expert-level Java development skills, with strong knowledge of modern frameworks, testing libraries, and build tools.
• Hands-on experience with AWS or comparable cloud platforms, including building cloud-native, containerized services on Kubernetes.
• Strong understanding of event-driven architectures and streaming platforms such as Kafka, with the ability to design, test, and operate event flows at scale.
• Experience with CI/CD, infrastructure automation, observability, and Site Reliability Engineering (SRE)/DevOps practices.
• Demonstrated experience using AI-assisted engineering tools, such as coding copilots, or building ML/LLM-enabled services, with a strong understanding of responsible AI practices.
• Strong collaboration and communication skills, with the ability to influence cross-functional stakeholders and work effectively across engineering, product, architecture, data, and AI teams.