Tech Lead - Graph Intelligence Platform

We are aiming to hire someone in the UK, Czechia or Italy.

Product Engineering at GraphAware offers a unique opportunity to build real-world intelligence systems that matter.

• Build with purpose: Your code will help law enforcement and analysts save lives and protect communities through better data insight.
  
• Innovative tech: Work with knowledge graphs, workflow engines, LLMs, and graph-native UIs pushing the boundaries of data analytics.
• Shape the future: Contribute to product direction and technical vision alongside a senior engineering team.
  
• True autonomy: Own your work, from ideation to deployment.Global mindset: Collaborate with a world-class team of engineers, data scientists, and product thinkers across Europe and beyond.
  
• Growth without bureaucracy: Develop your skills in a non-micromanaged, excellence-driven environment.

What you will be doing

As Tech Lead, you will own core parts of the platform layer of GraphAware Hume, our graph-powered analytics platform — the foundations that cut across every development group and that every feature team builds on. You'll be sought out across the organisation for technical guidance on graph architecture, and expected to anticipate issues at the product level before they surface. Neo4j sits at the heart of the product, we need someone who goes beyond using it well, and actively tracks new features, tests them against real workloads, and identifies where they can move the product forward. Working hands-on with Neo4j at the heart of the product, you will drive the architecture that lets us model, query, and scale the knowledge graphs our users depend on.

Your responsibilities will include:

Driving platform architecture, setting technical direction for the transversal foundations that feature teams across Hume build on, and shaping cross-cutting design decisions with the wider engineering group

• Owning our Neo4j strategy: actively tracking and hands-on testing of new releases and ecosystem tooling (GDS, APOC, etc.) to assess breaking changes, propose new product opportunities, and plan deliberate, scalable migrations.
• Optimizing Cypher queries and graph access patterns for latency, throughput, and scale
• Mentoring engineers and raising the team's technical bar (especially in Neo4j), without formal management authority
• Partner closely with Product Managers: to translate long-term product goals into scalable technical roadmaps

Designing secure, scalable access control systems for mission-critical environments

• Building APIs for intuitive user interaction with complex data

Orchestrating workflows to automate graph analytics, inference, and real-time insights

What you must know already and be excited to grow further

• Deep, hands-on Neo4j expertise, including advanced Cypher query performance optimization, profiling, and deep familiarity with the broader Neo4j ecosystem (e.g., GDS, APOC, drivers).
• Modelled real domains as property graphs and can reason about nodes, relationships, labels, and properties as a first-class design activity (relational modelling with e.g. PostgreSQL is a plus)
• Track record of leading architecture and technical direction for a team or product area, not just contributing to decisions made by others
• Proven ability to drive consensus: across engineering teams for large-scale architectural changes.
• Proven experience in backend systems (8+ years) with exposure to large-scale, complex applications and cross-functional teams
• Fluency in Java (or a strong JVM background you can bring to a Java codebase), with a deep understanding of modern software engineering principles, including:
  • Clean Architecture, Domain-Driven Design (DDD), and Test-Driven Development (TDD)
  • Advanced debugging and profiling techniques,
  • Writing composable, maintainable, and testable code
• Spring or similar frameworks with emphasis on building secure, modular, and scalable APIs
• Working knowledge of modern CI/CD pipelines, containerization (Docker), and automated deployment workflows
• Strong security mindset, with practical knowledge of secure software design and common vulnerabilities (e.g., OWASP)
• Comfortable with remote team collaboration, i.e. tools and practices for asynchronous communication

Bonus points for familiarity with:

• Knowledge graphs and GraphRAG: building knowledge graphs and grounding LLMs with graph-based retrieval (e.g. neo4j-graphrag, LangChain, LlamaIndex)
• Graph algorithms and analytics: (pathfinding, centrality, community detection) via Neo4j GDS, plus event-driven architectures, Kafka, or distributed systems
• Evolving large graph data models: over time: schema refactoring, migrations, and versioning as the domain grows
• Cloud-native development: observability, and performance tuning