Backend AI Developer (Java/Quarkus) - Hybrid Leça da Palmeira (2 days/week office)
Mid-level backend developer building Java/Quarkus microservices and APIs for a mobility-sector client in Iberia, on a hybrid basis (2 days/week in the Leça da Palmeira office). Day-to-day work spans features, bug fixes, automated testing, AI-assisted code reviews, and CI/CD troubleshooting using tools like GitLab Duo and Claude Code.
- Compensation
- Not disclosed
- Location
- Leça da Palmeira, Portugal
- Work setup
- Hybrid
- Seniority
- Middle
- Employment
- Not specified
- Experience
- 4+ years
- Category
- Backend
- Posted
Skills
Must have
- 4+ years of hands-on backend development experience
- Experience with Java (Quarkus is a plus)
- Practical experience using AI-assisted development tools (e.g. GitHub Copilot, GitLab Duo, Claude Code) in daily workflow
- Experience designing and building APIs and Java-based microservices running reliably at scale in production
- Experience writing automated unit and integration tests for backend systems
- Ability to understand the functional and business context of a feature before designing the technical solution
- Curiosity and willingness to experiment with new AI tools and integrate them responsibly
- Comfortable working in a fast-moving environment with evolving AI-assisted practices
- Strong attention to detail, critical thinking, and problem-solving skills
- B1 English (Intermediate) minimum, with good verbal and written communication
- Collaborative, adaptable, able to manage multiple priorities
Nice to have
- Experience with LLM-based integrations, RAG, or agent orchestration workflows
- Familiarity with MCP (Model Context Protocol) or similar AI tool/context integrations
- Exposure to AI-native development practices such as spec-driven development, custom prompt/skill libraries, automation workflows
Full description
Backend AI Developer (Java/Quarkus) - Hybrid Leça da Palmeira (2 days/week office)ABOUT THE OPPORTUNITY
Our client, a technology-driven company shaping the future of mobility across the Iberian market, is looking for a Mid-level Backend Developer to join their engineering team. This is a chance to work at the intersection of backend engineering and applied AI, using tools like GitLab Duo and Claude Code as part of your everyday workflow to build reliable, high-quality software faster.
PROJECT & CONTEXT
You will design, build, and maintain backend services and APIs using Java and Quarkus, while embracing an AI-first approach to how the team codes, tests, and reviews software. Day-to-day work includes solving backend tasks such as features, bug fixes, refactors, and integrations, writing automated unit and integration tests, participating in AI-assisted and peer code reviews, and troubleshooting CI/CD pipelines with the help of GitLab Duo. You'll collaborate closely with backend engineers, QA, and product to deliver dependable, well-tested software in a fast-moving, AI-enabled environment.
WHAT WE'RE LOOKING FOR (Required)
- 4+ years of hands-on backend development experience
- Experience with Java (Quarkus is a plus)
- Practical experience using AI-assisted development tools such as GitHub Copilot, GitLab Duo, Claude Code, or similar as part of a daily engineering workflow
- Experience designing and building APIs and Java-based microservices that run reliably at scale in production
- Experience writing automated unit and integration tests for backend systems
- Ability to understand the functional and business context of a feature before designing the technical solution
- Curiosity and willingness to experiment with new AI tools and integrate them responsibly into day-to-day development practices
- Comfortable working in a fast-moving environment where AI-assisted development practices are still evolving
- Strong attention to detail, critical thinking, and problem-solving skills
- B1 English (Intermediate) minimum, with good verbal and written communication skills
- Collaborative, adaptable, and able to manage multiple priorities effectively
NICE TO HAVE (Preferred)
- Experience with LLM-based integrations, Retrieval-Augmented Generation (RAG), or agent orchestration workflows
- Familiarity with MCP (Model Context Protocol) or similar tool/context integrations that connect AI assistants to internal systems
- Exposure to AI-native development practices beyond code completion, such as spec-driven development frameworks, custom prompt or skill libraries, and automation workflows