At a Glance
- Tasks: Lead the design and deployment of knowledge graph and GenAI systems for impactful clients.
- Company: Global AI and analytics firm at the forefront of knowledge graphs and generative AI.
- Benefits: Competitive pay, flexible work options, and opportunities for equity or bonuses.
- Other info: Mentorship opportunities and a dynamic environment for career growth.
- Why this job: Join an elite team and shape the future of AI in regulated industries.
- Qualifications: 5+ years in engineering or AI, with deep experience in graph technologies.
The predicted salary is between 63000 - 77000 £ per year.
- Knowledge Graph & Gen AI Lead
- London | Remote
- Up to £700 per day inside IR35
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 + Gen AI 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.
- Ship full systems
- Operate in regulated or industrial domains (e. g. manufacturing, life sciences, public sector)
- Embed client strategy and technical teams
- Stretching the frontier: hybrid KG + AI, graph + reasoning + M
- 🛠 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 / Graph RAG 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, Tiger Graph, Arango DB, Orient DB, 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
- Graph RAG 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 Data Scientist in England employer: Intelix.AI
As a leading global asset manager, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to excel. With competitive compensation packages, including a generous bonus structure and comprehensive family healthcare, we are committed to supporting your professional growth through continuous learning opportunities and innovative projects. Join us in a pivotal role where you will lead transformative technology initiatives, making a significant impact in the investment compliance landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Knowledge Graph & GenAI Data Scientist in England
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We think you need these skills to ace Knowledge Graph & GenAI Data Scientist in England
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Intelix.AI, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Intelix.AI. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Intelix.AI
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Intelix.AI!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
