Senior Software Engineer - GraphAware Hume

You’ll build secure, scalable backend services and APIs that make sophisticated data accessible and actionable. Your work will span graph analytics, workflow orchestration, access control, performance optimization, and technical architecture. You’ll contribute to products designed to help analysts and organizations uncover meaningful insights from connected data. Working alongside experienced engineers, data scientists, and product specialists, you’ll have significant ownership over your work from design through deployment. The environment is remote-first, collaborative, and technically ambitious, with room to influence both architecture and product direction. You’ll also have opportunities to expand into graph technologies, distributed systems, cloud-native engineering, and AI-driven applications. Accountabilities

• Build and maintain backend APIs that enable intuitive and efficient interaction with complex graph and analytical data.
• Design and implement secure, scalable access-control systems suitable for mission-critical environments and sensitive data.
• Develop and orchestrate workflows that automate graph analytics, inference, and real-time insight generation.
• Optimize application performance and reliability while collaborating with other engineers to deliver seamless user experiences.
• Contribute to system architecture, technical design, and engineering decisions across the product.
• Develop clean, maintainable, composable, and well-tested software using modern engineering practices.
• Collaborate closely with cross-functional and distributed teams to translate product needs into robust technical solutions.
• Take ownership of projects from ideation through implementation and deployment, working with a high degree of autonomy.
• Contribute to continuous improvement of engineering practices, security, observability, and system scalability., * Opportunity to work on technically challenging products involving knowledge graphs, workflow engines, LLMs, and graph-native user interfaces.
• Significant autonomy and ownership from ideation through deployment.
• Opportunity to influence product direction and technical architecture alongside a senior engineering team.
• Collaboration with engineers, data scientists, and product professionals across Europe and beyond.
• Meaningful work supporting advanced data analytics and intelligence applications.
• Strong opportunities for professional and technical growth in a non-micromanaged environment.
• Inclusive and collaborative culture focused on relationships, innovation, customer success, and continuous learning.
• Opportunity to work with technologies at the intersection of graph data, distributed systems, cloud engineering, and AI.

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Häufige Suchvorgänge

• 8+ years of professional experience developing backend systems, ideally within large-scale or technically complex applications.
• Strong proficiency in Java and a deep understanding of modern software engineering principles, including Clean Architecture, Domain-Driven Design (DDD), and Test-Driven Development (TDD).
• Advanced debugging and profiling skills, with the ability to diagnose complex application and performance issues.
• Experience with Spring or a similar framework, particularly for developing secure, modular, and scalable APIs.
• Strong understanding of data modeling across relational databases such as PostgreSQL; experience with graph-based data models is highly valuable.
• Working knowledge of modern CI/CD practices, Docker, automated deployment workflows, and production software delivery.
• Strong security mindset with practical knowledge of secure software development and common vulnerabilities such as those covered by OWASP.
• Excellent communication and collaboration skills, with experience working effectively in remote and distributed teams.
• Ability to work autonomously, contribute to technical direction, and communicate clearly with both technical and non-technical stakeholders.
• Familiarity with graph technologies such as Cypher, Neo4j, or knowledge graphs is a strong advantage.
• Experience with event-driven architectures, Kafka, distributed systems, cloud-native development, observability, or performance tuning is beneficial.
• Exposure to LLMs or integrating AI/ML capabilities into production systems is a plus.