Senior Backend Developer (Java/Spring Boot, Agentic LLMs)

Accountabilities:

Backend development: Design, develop, maintain, and optimize backend services using Java and Spring Boot, delivering reliable, scalable, and maintainable software.
End-to-end feature delivery: Take ownership of software features throughout their lifecycle, from understanding requirements and implementation to testing, debugging, deployment, and ongoing improvement.
API development and integration: Build and maintain REST APIs that support web applications, mobile experiences, and integrations with external systems.
Distributed systems engineering: Develop and improve distributed services, ensuring reliability, scalability, and effective communication between system components.
Event-driven architecture: Implement asynchronous processing and event-driven workflows using Apache Kafka or comparable messaging and streaming technologies.
Database management: Design and maintain relational data models using PostgreSQL and Hibernate, with a focus on data integrity, query efficiency, and application performance.
Agentic AI and LLM integration: Apply practical knowledge of large language models, retrieval-augmented generation (RAG), agent-tool interactions, and LLM orchestration to develop intelligent backend capabilities and automation workflows.
AI-assisted development: Use tools such as Cursor, Claude Code, and GitHub Copilot to accelerate development while maintaining high standards for code quality, testing, security, and maintainability.
Engineering quality: Write clean, well-tested code, apply sound functional programming principles, and contribute to debugging, code reviews, and continuous improvement.
Cross-functional collaboration: Work closely with product managers and fellow engineers to translate requirements into effective technical solutions and deliver meaningful business outcomes.
Technical optimization: Identify opportunities to improve system performance, reliability, maintainability, and development efficiency through modern engineering practices.
Requirements:
Professional experience: At least six years of hands-on Java backend development experience, ideally using Java 17 or a comparable modern version.
Backend frameworks: Strong experience with Spring Boot 2.x or 3.x and Hibernate 5.x or 6.x, including the development and maintenance of production-grade applications.
Distributed systems and APIs: Proven experience building scalable distributed systems, developing REST APIs, and integrating services across complex application environments.
Database expertise: Solid knowledge of PostgreSQL, relational database modeling, and data persistence using Hibernate or related technologies.
Event-driven development: Practical experience implementing event-driven architectures and asynchronous processing using Apache Kafka or similar messaging and streaming platforms.
Functional programming: Strong familiarity with functional programming principles, including immutability, pure functions, and concurrency-aware design.
LLMs and agentic workflows: Hands-on familiarity with LLM-based applications and agentic workflows, including RAG pipelines, tool interactions, and orchestration. You should be able to explain concrete implementations and the engineering decisions behind them.
AI coding tools: Regular use of AI-assisted development tools such as Cursor, Claude Code, or GitHub Copilot, combined with the judgment needed to validate generated code, write tests, and maintain software quality.
Development tools and delivery: Proficiency with Git, Maven, testing frameworks, debugging techniques, and end-to-end software delivery.
Communication and teamwork: Strong collaboration skills and professional fluency in English at B2 level or above, with C1 preferred.
Preferred AI experience: Familiarity with the Model Context Protocol (MCP), autonomous agents, or multi-agent workflows is an advantage.
Additional programming knowledge: Experience with Scala, Kotlin, or functional Java libraries such as Vavr is considered a plus.
Search and performance technologies: Familiarity with Elasticsearch, vector search, embeddings, Redis, and performance optimization is beneficial.
Cloud and DevOps: Experience with Docker, Kubernetes, AWS, Terraform, and CI/CD pipelines is an advantage.
Applied AI integration: Previous experience integrating LLM-powered features into existing backend services is highly desirable.
Remote work eligibility: Ability to work fully remotely from an eligible European country, subject to contractual and country-specific requirements.
Benefits:
Fully remote work: Work remotely from an eligible location in Europe, without the need for regular office attendance.
International engineering environment: Collaborate with a distributed team building a sophisticated technology platform for the global business aviation industry.
Technical ownership: Take responsibility for meaningful backend features and contribute directly to engineering quality and platform development.
Modern technology stack: Work with Java, Spring Boot, distributed systems, event-driven architectures, and emerging agentic AI technologies.
Practical AI innovation: Explore and implement LLM-powered workflows and AI-assisted development practices in real-world production systems.
Professional growth: Strengthen your expertise in scalable backend engineering, AI integration, and modern software delivery practices.
Collaborative culture: Work closely with product and engineering colleagues in an environment that values code quality, pragmatic problem-solving, and continuous improvement.