Role: Senior Java Engineer Type: Permanent Location: Nenagh (Onsite) Your Responsibilities: Architect, develop, and deliver high-quality microservices and event-driven capabilities that underpin modern digital experiences.
Collaborate closely with architecture, product, data science, and AI platform teams to weave machine learning and AI-assisted workflows into customer-facing and operational journeys.
Spearhead the breakdown and modernisation of legacy components using domain-driven design principles, strangler patterns, and AI-accelerated refactoring approaches.
Build, instrument, and document systems in a way that enables AI copilots and autonomous runbooks to safely observe, learn, and take action — covering telemetry, feature flags, and guardrails.
Champion engineering excellence through considered design reviews, automated testing, chaos and resilience practices, and well-defined reliability standards.
Enhance the developer experience by delivering automated pipelines, infrastructure-as-code, policy-as-code, and AI-powered tooling that tighten feedback loops.
Guide and develop engineers in AI-first ways of working, encompassing prompt literacy, copilot pair-programming, responsible-use principles, and a disciplined approach to experimentation.
Strike the right balance between transformation goals and delivery commitments through pragmatic, data-informed engineering decisions and proactive risk communication.
Take ownership of the full spectrum of tasks within a modern delivery pipeline, including validation activities (such as unit, component, system integration, and regression testing) and infrastructure activities (such as infrastructure-as-code within automated pipelines).
Design and implement monitoring and logging solutions that enable best-in-class observability of enterprise applications across the production environment.
What You'll Bring: 6+ years experience of delivering software within complex, distributed, and highly regulated environments.
Expert-level proficiency in Java, alongside fluency in modern frameworks, testing libraries, and build tooling.
Practical experience with AWS or an equivalent cloud platform, including building cloud-native, containerised services on Kubernetes.
Solid understanding of event-driven architectures and streaming platforms such as Kafka, with the ability to model, test, and operate event flows at scale.
Hands-on experience with CI/CD pipelines, infrastructure automation, observability stacks, and Site Reliability/DevOps practices.
Demonstrated use of AI-assisted engineering tools (such as GitHub Copilot or internal copilots), or direct experience building ML/LLM-enabled services — along with a thoughtful, responsible approach to applying AI.
Strong interpersonal and communication skills, with the ability to influence cross-functional stakeholders and navigate enterprise governance structures.
Note: This role is on site role.