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- Tasks: Lead the design and deployment of knowledge graph and GenAI systems for impactful clients.
- Company: Global AI & analytics firm at the forefront of technology.
- Benefits: Competitive pay, flexible work options, and opportunities for equity or bonuses.
- Why this job: Join an elite team and shape the future of AI and data integration.
- Qualifications: 5+ years in engineering or AI roles with expertise in graph technologies.
- Other info: Mentor junior engineers and enjoy a dynamic, fast-paced environment.
Global AI & analytics firm operating at the intersection of knowledge graphs, generative AI, and enterprise transformation. This role requires you to embed graph intelligence into mission-critical systems enabling explainable AI, unified data views, and advanced reasoning across regulated industries and industrial domains. You will drive the design, build, and deployment of knowledge graph + GenAI systems for high-impact clients. You’ll be part of a small elite team, bridging data, AI, and business outcomes — from model scoping through to production launch.
Responsibilities
- Lead KG schema & ontology design across domains (assets, risk, supply chain, compliance)
- Build ingestion pipelines (ETL / streaming / CDC) and entity resolution for graph population
- Author complex queries (Cypher, GSQL, AQL, SPARQL etc. depending on stack)
- Integrate knowledge graph retrieval & reasoning into LLM / RAG / GraphRAG systems
- Develop and evaluate graph ML / embedding models (link prediction, anomaly detection)
- Optimize graph performance, scaling, and query efficiency
- Liaise with client stakeholders: translate business problems into graph solutions
- Mentor junior engineers, contribute to propositions, and support POCs
Must-Have Skills & Experience
- 5+ years in engineering, data, or AI roles
- Deep experience with at least one graph technology: Neo4j, TigerGraph, ArangoDB, OrientDB, or Stardog
- Proficiency in query languages (Cypher, GSQL, AQL, SPARQL, etc.)
- Strong background in pipelines, ETL, and entity resolution
- Exposure to integrating KG + LLM or RAG architectures
- Experience with graph algorithms, embeddings, or GNNs
- Cloud & production engineering literacy (AWS/Azure/GCP, containerization, CI/CD)
- Excellent communication skills — able to explain complex graph/AI concepts to non-technical audiences
Nice-to-Have / Bonus Assets
- Experience with GraphRAG or KG-backed LLM retrieval
- Semantic web / ontology skills (RDF/OWL/SHACL)
- Prior consulting or client delivery background
- Graph visualization / UI experience (Linkurious, Bloom, Ogma)
- Graph DB certifications (Neo4j, Stardog, etc.)
- High visibility & critical client impact
- Exposure to cutting-edge hybrid AI / KG architectures
- Autonomy, ownership, and fast learning
Competitive compensation + meaningful equity or bonus scheme. Flexible / hybrid work arrangement.
Knowledge Graph & GenAI Lead employer: Intelix.AI
Contact Detail:
Intelix.AI Recruiting Team
We think you need these skills to ace Knowledge Graph & GenAI Lead
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Knowledge Graph & GenAI Lead role. Highlight your experience with graph technologies and AI, and show us how your skills align with our needs. A personal touch goes a long way!
Showcase Your Skills: Don’t just list your skills; demonstrate them! Use specific examples from your past work that showcase your expertise in graph schema design, query languages, and pipeline building. We want to see how you’ve tackled challenges in the past.
Be Clear and Concise: When writing your application, keep it clear and to the point. Avoid jargon unless necessary, and make sure your key achievements stand out. We appreciate straightforward communication, especially when it comes to complex topics like AI and data.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Intelix.AI
✨Know Your Graph Tech
Make sure you brush up on your knowledge of graph technologies like Neo4j or TigerGraph. Be ready to discuss your experience with these tools and how you've used them in past projects. This will show that you’re not just familiar with the tech, but that you can apply it effectively.
✨Master the Query Languages
Get comfortable with query languages such as Cypher, GSQL, and SPARQL. Prepare to demonstrate your ability to author complex queries during the interview. You might even be asked to solve a problem on the spot, so practice writing queries beforehand!
✨Showcase Your Communication Skills
Since you'll need to explain complex concepts to non-technical stakeholders, practice simplifying your explanations. Think of examples from your past work where you successfully communicated technical details to a diverse audience. This will highlight your ability to bridge the gap between tech and business.
✨Prepare for Real-World Scenarios
Expect questions about how you would approach real-world problems in regulated industries. Think about specific challenges you've faced and how you solved them using knowledge graphs and AI. This will demonstrate your practical experience and problem-solving skills.