Engineering Manager - Java Full Stack & AI

• 7+ years of commercial software engineering experience.
• Expert-level knowledge of Java (17+) and modern backend development practices.
• Strong hands-on experience with Spring Boot and the Spring ecosystem.
• Commercial Full Stack development experience with Angular and/or React.
• Solid understanding of modern JavaScript/TypeScript frameworks and frontend development.
• Experience designing and developing REST APIs and microservices-based solutions.
• Strong knowledge of software architecture, system design, and integration patterns.
• Experience working with distributed systems, event-driven architectures, and scalable applications.
• Commercial experience with AI-powered solutions, including Large Language Models (LLMs), AI agents, or agentic workflows.
• Experience using AI-assisted development tools such as GitHub Copilot or similar.
• Ability to assess the technical and business feasibility of AI initiatives.
• Understanding of AI adoption from business value and ROI perspectives.
• Commercial experience with at least one major cloud platform (Azure, AWS, or GCP).
• Practical knowledge of DevOps practices, CI/CD pipelines, and Infrastructure as Code (IaC).
• Strong understanding of Software Development Lifecycle (SDLC) and Product Development Lifecycle (PDLC).
• Experience working in Agile delivery environments.
• Ability to translate business requirements into scalable technical solutions.
• Experience mentoring engineers and/or providing technical leadership.
• Strong stakeholder management and client-facing communication skills.
• Experience supporting recruitment activities, technical interviews, and competency assessments.

Nice to have:

• Practical experience with Terraform, Kubernetes, Docker, or similar containerization and infrastructure technologies.
• Experience working with Kafka and event-driven architectures.
• Knowledge of Retrieval-Augmented Generation (RAG) and related AI implementation patterns.
• Familiarity with AI orchestration frameworks and enterprise AI integrations.
• Experience supporting presales activities, technical discovery workshops, and solution design.
• Background in Financial Services, Banking, or FinTech projects.
• Experience working in consulting, outsourcing, or multi-client environments.
• Additional foreign language skills, particularly German and/or French.
• Advanced knowledge of DevOps practices and Infrastructure as Code (IaC).

• Lead and mentor engineering teams while maintaining technical credibility.
• Participate in architecture discussions and technical decision-making.
• Support project delivery and resolve complex technical or organizational challenges.
• Act as a trusted technical advisor for clients and stakeholders.
• Evaluate AI opportunities and recommend solutions based on business value and feasibility.
• Support technical recruitment, interviewing, and competency development.
• Collaborate with Hiring Managers on team structures and capability planning.
• Contribute to presales, estimation, and solution design activities.
• Identify training needs and drive knowledge-sharing initiatives across teams.
• Foster engineering excellence, continuous improvement, and long-term business growth.