Sr Java Developer

About

As a Senior Software Engineer on you will pair deep engineering expertise with AI- assisted delivery to build the next generation of event-driven, cloud-native payment services. You will architect and ship resilient platforms, champion responsible AI adoption, and help teams move faster while staying compliant and secure.

What you will do:

• Design, build, and ship high-quality microservices and event-driven capabilities that power modern experiences.
• Partner with architecture, product, data science, and AI platform teams to embed machine learning and AI-assisted workflows in customer and operational journeys.
• Lead the decomposition and modernisation of legacy components, applying domain-driven design, strangler patterns, and AI-accelerated refactoring techniques.
• Curate, instrument, and document systems so AI copilots and autonomous runbooks can observe, learn, and act safely (telemetry, feature flags, guardrails).
• Drive engineering excellence through thoughtful design reviews, automated testing, chaos/resilience practices, and codified reliability standards.
• Improve developer experience with automated pipelines, infrastructure-as-code, policy-as-code, and AI-enabled tooling that shorten feedback loops.
• Coach and mentor engineers on AI-first ways of working: prompt literacy, pair-programming with copilots, responsible-use guidelines, and experimentation discipline.
• Balance transformation ambition with delivery commitments by making pragmatic, data-informed engineering trade-offs and communicating risks early.

What you will need to have:

• Proven experience delivering software in complex, distributed, highly regulated environments.
• Expert-level Java skills plus fluency with modern frameworks, testing libraries, and build tooling.
• Hands-on experience with AWS (or comparable cloud) and building cloud-native,containerised services on Kubernetes
• Working knowledge of event-driven architectures and streaming platforms such as Kafka; able to model, test, and operate event flows at scale.
• Experience with CI/CD, infrastructure automation, observability stacks, and Site Reliability/DevOps practices.
• Demonstrated use of AI-assisted engineering tools (e.g., GitHub Copilot, internalcopilots) or building ML/LLM-enabled services; comfort applying AI responsibly.
• Strong collaboration and communication skills with the ability to influence cross-functional partners and navigate