Developer – AI-Enabled Delivery

Mindbox is a tech-driven company connecting top IT talents with technology projects for leading enterprises across Europe. They are building next-generation Collateral and Facility Management solutions leveraging AI-enabled SDLC practices, strong engineering standards, and modern integration capabilities.

• Solid hands-on experience in Java microservices development (Spring Boot) within enterprise environments
• Proficiency in RDBMS (Oracle, PostgreSQL): schema design, query optimization, performance tuning
• Strong understanding of API design, RESTful integration patterns, messaging/event-driven systems
• Experience with CI/CD pipelines, quality gates, and DevSecOps practices (Jenkins, GitLab, Sonar, SAST/DAST scanning)
• Expertise in automated testing practices: JUnit, Mockito, Testcontainers, contract/API testing
• Hands-on exposure to GCP (Google Cloud Platform) or other cloud environments
• Familiarity with GenAI tools and patterns in software development (e.g., LLMs, RAG, agent workflows) and governance principles
• Ability to design scalable solutions under complex delivery and regulatory constraints

Nice to have:

• Experience with regulated financial platforms requiring strong controls and audit readiness
• Knowledge of containerization, Kubernetes, and service mesh patterns
• Familiarity with observability stacks and resilience engineering practices
• Hands-on experience implementing AI-enabled SDLC guardrails and productivity metrics
• Prior involvement in GenAI prototyping – including RAG pipelines, eval frameworks, and prompt lifecycle management

• Build, test, release, and support Java microservices and related components
• Contribute to solution design and integration patterns in alignment with target architecture
• Proactively identify and resolve technical risks, dependencies, and cross-stream blockers
• Follow and improve engineering standards: coding practices, branching, CI/CD quality gates
• Deliver robust automated tests (unit, contract, integration) to maintain measurable quality
• Participate in design, code, and security reviews, remediating findings promptly
• Use AI-assisted development tools (e.g., GitHub Copilot) responsibly with strong security and IP governance
• Apply reviewed guardrails for AI-generated code: secure coding checks, traceability, auditability, LLM safe usage for code generation, Retrieval-Augmented Generation (RAG) for validated responses, Agent-style workflows with human-in-the-loop controls
• Apply security-by-design principles: secure coding, secrets management, vulnerability remediation
• Build production-ready services with observability (logs, metrics, traces), performance testing, and incident readiness
• Work closely with Tech Leads, QA, SRE, and platform teams across multiple streams
• Promote a culture of shared accountability, continuous improvement, and engineering excellence