Tech Lead, Backend - GraphAware Hume

Accountabilities

• • Drive platform architecture and technical direction, owning the transversal foundations that feature teams build upon and influencing cross-cutting architectural decisions across the engineering organization.
  • Own the graph technology strategy, continuously evaluating new releases, ecosystem tooling, and capabilities, while testing them against real workloads, anticipating breaking changes, and planning scalable migrations.
  • Optimize graph performance and scalability by designing and refining Cypher queries, graph access patterns, data models, and database architecture for latency, throughput, and reliability.
  • Lead backend engineering initiatives, building secure, modular, scalable APIs and platform services that provide intuitive access to complex graph-based data.
  • Design secure access-control systems suitable for mission-critical environments, applying strong security principles throughout backend architecture and implementation.
  • Orchestrate graph-powered workflows that automate analytics, inference, and real-time insight generation.
  • Partner with Product Managers and engineering stakeholders to translate long-term product objectives into practical technical strategies, roadmaps, and architectural priorities.
  • Provide technical mentorship and influence, raising engineering standards and helping teams make sound architectural decisions without relying on formal management authority.
  • Drive consensus across teams for significant architectural changes, clearly communicating trade-offs, risks, and long-term implications.
  • Anticipate platform-level challenges before they affect product teams, proactively identifying opportunities to improve reliability, scalability, maintainability, and developer experience.
  • Contribute hands-on to development and delivery, applying modern engineering practices across design, implementation, testing, debugging, profiling, CI/CD, and deployment.
  • Collaborate effectively in a distributed environment, using asynchronous communication and remote-working practices to maintain alignment across geographically dispersed teams.

  Requirements:

  • 8+ years of backend engineering experience, including work on large-scale, complex applications and collaboration across multiple technical and functional teams.
  • Deep, hands-on Neo4j expertise, including advanced Cypher optimization, query profiling, graph access patterns, and familiarity with the broader ecosystem such as Graph Data Science (GDS), APOC, and Neo4j drivers.
  • Strong graph data modelling experience, with the ability to model real-world domains using nodes, relationships, labels, and properties as core architectural concepts; relational database experience, such as PostgreSQL, is a plus.
  • Proven technical leadership experience, including ownership of architecture and technical direction for a team, platform, or product area rather than simply contributing to decisions made by others.
  • Strong Java or JVM expertise, with the ability to work confidently in a Java codebase and apply modern software engineering principles such as Clean Architecture, Domain-Driven Design (DDD), and Test-Driven Development (TDD).
  • Experience with Spring or comparable backend frameworks, particularly for developing secure, modular, maintainable, and scalable APIs.
  • Advanced debugging and profiling skills, with a track record of diagnosing complex technical issues and improving system performance.
  • Strong software engineering fundamentals, including writing composable, maintainable, testable code and designing systems for long-term scalability.
  • Practical security expertise, including secure software design, common vulnerabilities, and OWASP principles.
  • Working knowledge of CI/CD and cloud-native practices, including Docker, automated deployment workflows, and modern observability approaches.
  • Ability to influence without formal authority, build consensus across engineering teams, and guide organization-wide architectural change.
  • Strong communication and collaboration skills, particularly in distributed and asynchronous environments.
  • Bonus: Experience with knowledge graphs, GraphRAG, or grounding LLMs using graph-based retrieval technologies such as neo4j-graphrag, LangChain, or LlamaIndex.
  • Bonus: Familiarity with graph algorithms and analytics, including pathfinding, centrality, and community detection, as well as event-driven architectures, Kafka, or distributed systems.
  • Bonus: Experience evolving large graph data models through schema refactoring, migrations, and versioning.
  • Bonus: Exposure to cloud-native development, observability, and performance tuning.

  Benefits:

  • Competitive compensation package aligned with your experience and expertise.
  • Flexible, remote-friendly working environment designed for distributed collaboration.
  • High level of autonomy and ownership, with the opportunity to shape technical direction and product architecture.
  • Opportunity to work on knowledge graphs, graph analytics, workflow engines, LLM-related technologies, and graph-native user experiences.
  • Meaningful work contributing to intelligence systems designed to help organizations make better decisions from complex data.
  • Collaboration with experienced engineers, data scientists, product leaders, and technical specialists across Europe and beyond.
  • Strong opportunities for professional growth in an environment focused on technical excellence rather than bureaucracy or micromanagement.
  • Inclusive and collaborative culture that values relationships, openness, intellectual honesty, innovation, and customer success.
  • Opportunity to influence the future of graph technology and intelligent applications at significant scale.