Middle Java Engineer | Generative AI, LLMs & Microservices

Project description

Our Surveillance and Regulatory Technology division delivers innovative solutions that protect financial and reputational interests from potentially criminal or inappropriate behaviour. Through real-time sanction and embargo filtering, operational risk controls, and sophisticated fraud detection, our systems protect both clients and the organization, ensuring compliance with global regulations.

We are launching several new AI initiatives to integrate advanced machine learning and cognitive capabilities into our platforms. We are seeking a highly analytical Senior Software Engineer to participate actively in every phase of the software development lifecycle. In this role, you will help design and build modern applications, with a strong focus on implementing Large Language Models (LLMs), RAG systems, and agentic workflows.

Responsibilities

Application Development: Collaborate within a global, distributed team to build and deliver robust, scalable, and secure microservices and applications.

AI & LLM Integration: Actively contribute to the development of new AI features, implementing LLM-based solutions, Retrieval-Augmented Generation (RAG) pipelines, and LLM agents.

Full SDLC Participation: Engage in the entire software development lifecycle, from analysing requirements and brainstorming technical solutions to writing clean code, testing, and deployment.

Quality & Automation: Embrace automated unit/integration testing (TDD/BDD) and modern CI/CD practices as standard engineering disciplines.

Skills

• AI & Emerging Technologies
• Generative AI & LLMs: Solid conceptual and practical understanding of Large Language Models (LLMs).
• Advanced AI Architectures: Knowledge of Retrieval-Augmented Generation (RAG), LLM agents, and agentic architectures.
• AI Frameworks & Tools: Exposure to or experience with Spring AI, Python-based AI frameworks (e.g., LangChain, LlamaIndex), and cloud AI platforms such as Google Cloud Vertex AI.
• Backend Engineering & Language Skills
• Java & Spring Boot (Strong Advantage): Prior experience with modern Java (Java 17/21) and the Spring Boot framework is highly preferred and considered a major asset, though candidates with strong backgrounds in other enterprise languages (such as Python) who are willing to work in a hybrid environment are welcome.
• Message-Driven Systems: Experience with data streaming and messaging technologies like Apache Kafka, IBM MQ, or equivalent tools.
• Cloud & DevOps: Practical experience with cloud-native application development (Google Cloud Platform experience is a strong plus) and container technologies (Docker, Kubernetes, or OpenShift).
• Mindset & Methodology
• 3+ years of software engineering experience with a highly analytical and problem-solving mindset.
• Experience working in Agile environments (Scrum, Jira, Confluence).
• Commitment to high-quality code, testing standards (TDD/BDD), and modern CI/CD build chains (Maven, Gradle, Git, Jenkins/TeamCity).