Jobgether
Tech Lead, Backend - GraphAware Hume

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Tech Lead, Backend - GraphAware Hume
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Tech Lead, Backend - GraphAware Hume based in United Kingdom.
This is a senior technical leadership role focused on the platform foundations of a graph-powered analytics product.
- You’ll shape backend architecture and technical direction across capabilities used by multiple engineering teams.
- The role combines hands-on development with deep expertise in graph databases, APIs, security, and scalable systems.
- You’ll be the technical authority for graph architecture, continuously evaluating new technologies and opportunities to improve the platform.
- You’ll work closely with engineers and Product Managers to turn product goals into robust, long-term technical roadmaps.
- The environment is highly collaborative and remote-friendly, with significant autonomy and influence without formal people-management responsibilities.
- Your work will help deliver intelligence systems that enable organizations to extract meaningful insights from complex connected data.
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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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.


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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.
How Jobgether Works
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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