Developer – AI-Enabled Delivery

At Mindbox we connect top IT talents with technology projects for leading enterprises across Europe. oin our team building Global Collateral and Facility Management capabilities for a mission-critical platform replacement program. The goal is to deliver a modern in-house solution leveraging Java microservices, cloud technologies, and AI-assisted engineering practices , with strong governance and quality controls. This is a hands-on engineering role focused on building, integrating, and deploying secure, production-grade services at pace. You will work across multiple delivery streams in collaboration with Tech Leads, architects, platform, QA, and operations teams, applying modern AI-enabled SDLC techniques while adhering to enterprise security and compliance standards. Sounds like your kind of challenge? What you get in return Flexible cooperation model – choose the form that suits you best (B2B, employment contract, etc.) Hybrid work setup – 2 days per week from the office Collaborative team culture – work alongside experienced professionals eager to share knowledge Continuous development – access to training platforms and growth opportunities Comprehensive benefits – including Interpolska Health Care, Multisport card, Warta Insurance, and more High quality equipment – laptop and essential software provided
Requirements:
4 - 8 years of experience. Strong hands-on experience with Java microservices development (Spring Boot). Solid understanding of RDBMS (Oracle/PostgreSQL): schema design, performance tuning, and transaction handling. In-depth knowledge of unit testing, integration testing, contract testing (JUnit, Mockito, Testcontainers). Proven experience with CI/CD pipelines (Jenkins/GitLab) and quality gates (Sonar, SAST/DAST scanning). Familiarity with integration patterns (REST APIs, event-driven messaging). Experience in technical design , with pragmatic trade-offs under delivery constraints. Hands-on experience with cloud platforms (GCP) . Practical exposure to GenAI concepts and tools (LLMs, RAG, agentic workflows) and associated governance. Nice to have: Previous work in regulated industries with strong audit and operational control. Knowledge of cloud-native patterns : containers, Kubernetes, service mesh, observability tooling. Exposure to performance engineering and resilience testing . Prior participation in AI-enabled SDLC adoption with governance frameworks. Hands-on with GenAI prototyping (prompt engineering, RAG pipelines, evaluation methods). Joining this project you’ll become part of Mindbox – a tech-driven company where consulting, engineering, and talent meet to build meaningful digital solutions. We’ll back you up every step of the way, accelerate your development, and ensure your skills make a difference.
Must have: Java, Microservices, Spring Boot, RDBMS, Oracle, Unit testing, Testing, JUnit, Mockito, CD pipelines, GitLab, SAST, DAST, REST API, Cloud platform
Nice to have: Audit, Kubernetes, Service mesh, SDLC, Prototyping
Daily tasks: - Design, build, test, and release Java microservices and related components in an enterprise environment.
– Contribute to solution design and integration patterns, ensuring alignment with architecture and non-functional requirements.
– Identify and mitigate technical risks and dependencies impacting delivery.
– Apply and enhance engineering standards, including coding practices, branching, TDD, CI/CD pipelines, and automated quality gates.
– Deliver comprehensive unit, integration, and contract tests (JUnit, Mockito, API testing).
– Participate in peer reviews for design, code, and security, remediating issues promptly.
– Use AI-assisted tooling (e.g., GitHub Copilot) to accelerate delivery responsibly, meeting security and traceability standards.
– Apply guardrails for AI-generated code, including review, audit, and IP compliance.
– Contribute to safe GenAI integration patterns, such as LLM usage, retrieval-augmented generation (RAG), and agent workflows with human review.
– Embed security-by-design, including vulnerability management and secure coding practices.
– Ensure production readiness: observability, logging, monitoring, performance testing, and incident support.
– Work with cross-functional teams to deliver integrated outcomes and improve developer velocity.
– Promote an inclusive, collaborative culture based on engineering excellence and innovation.