At a Glance
- Tasks: Lead the design and development of cutting-edge AI knowledge graphs.
- Company: Join a pioneering AI-driven tech company with a focus on innovation.
- Benefits: Competitive salary, flexible working, and significant ownership in projects.
- Other info: Fast-paced environment with direct access to leadership and career growth.
- Why this job: Shape the future of intelligent enterprise products and make a real impact.
- Qualifications: Experience in Neo4j, Python, and knowledge graph integration required.
The predicted salary is between 150000 - 150000 £ per year.
We’re partnering with an AI-driven technology company looking to hire an AI Knowledge Graph/ Ontology Lead to build and scale the knowledge graph layer underpinning a new generation of intelligent enterprise products. This is a senior, hands-on leadership role for someone who has real experience designing and shipping production knowledge graphs, not just conceptual ontology work.
You’ll be responsible for shaping a graph and ontology platform that powers:
- AI retrieval and RAG workflows
- Entity linkage and reasoning systems
- Cross-domain and temporal knowledge modeling
- Regulatory and compliance intelligence products
- Agentic AI applications
The role combines architecture, hands-on engineering, and team leadership. You’ll work closely with AI/ML engineers to turn complex, unstructured information into structured, queryable intelligence that directly feeds live AI systems.
Key experience includes:
- Strong Neo4j and Cypher expertise in production environments
- Deep ontology / taxonomy modeling experience
- Python engineering skills
- Knowledge graph integration with LLMs, RAG, or vector search systems
- Experience balancing formal semantics with pragmatic implementation
- Ability to lead technically while remaining hands-on
Additional experience in areas such as RDF/OWL, inference engines, entity resolution, legal/regulatory data, ESG, healthcare, or pharmaceutical domains would be highly valuable.
The company offers:
- A highly technical AI environment
- Significant ownership and architectural influence
- Fast decision-making and direct access to leadership
- Strong adoption of AI-assisted development tooling
- Flexible working arrangements and competitive compensation
Ideal for someone excited by the challenge of building the intelligence layer behind complex AI products at scale. Please apply for more details.
AI Knowledge Graph Lead employer: DeepRec.ai
Join a pioneering AI-driven technology company that values innovation and technical excellence, offering a dynamic work culture where your contributions directly shape the future of intelligent enterprise products. With flexible working arrangements, competitive compensation, and significant opportunities for professional growth, this role is perfect for those eager to lead and innovate in a highly technical environment. Experience the thrill of building cutting-edge knowledge graph solutions while enjoying direct access to leadership and a collaborative team atmosphere.
StudySmarter Expert Advice🤫
We think this is how you could land AI Knowledge Graph Lead
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and knowledge graph space on LinkedIn. Join relevant groups and participate in discussions to get your name out there. You never know who might have a lead on that perfect role!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous work with knowledge graphs, especially any hands-on projects. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for those interviews! Brush up on your Neo4j and Cypher skills, and be ready to discuss your experience with ontology modeling. Practice explaining complex concepts in simple terms – it shows you really understand your stuff.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace AI Knowledge Graph Lead
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with knowledge graphs and ontology work. We want to see how your skills align with the role, so don’t be shy about showcasing your Neo4j and Cypher expertise!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how your hands-on leadership experience can contribute to our team. Let us know what excites you about building intelligent enterprise products.
Showcase Relevant Projects:If you've worked on projects involving AI retrieval, entity linkage, or knowledge modeling, make sure to mention them. We love seeing real-world applications of your skills, so share specific examples that demonstrate your impact.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it makes the process smoother for everyone involved!
How to prepare for a job interview at DeepRec.ai
✨Know Your Graphs
Make sure you brush up on your Neo4j and Cypher skills before the interview. Be ready to discuss specific projects where you've designed and implemented knowledge graphs, as this will show your hands-on experience and technical expertise.
✨Showcase Your Leadership
Prepare examples that highlight your leadership style and how you've successfully led teams in previous roles. Discuss how you balance being hands-on with guiding your team, as this is crucial for the role.
✨Understand the Business Context
Familiarise yourself with the company's products and how knowledge graphs can enhance their AI capabilities. Being able to connect your technical skills to their business needs will demonstrate your strategic thinking.
✨Prepare for Technical Questions
Expect deep technical questions related to ontology modeling, entity resolution, and integration with LLMs. Practise explaining complex concepts in simple terms, as this will showcase your ability to communicate effectively with both technical and non-technical stakeholders.
