Semantic Data Architect (Ontologist, Knowledge Graph)

Roles & Responsibilities

• Design and build ontologies (knowledge models) that organize Dell's business information in a structured way.
• Connect data from different systems so that all information is consistent and easy to understand.
• Create relationships between products, customers, services, and other business data to improve search and AI capabilities.
• Work closely with business teams to understand their requirements and convert them into structured knowledge models.
• Ensure data is organized according to industry standards such as RDF, OWL, and SPARQL.
• Improve enterprise search, analytics, and AI-driven applications by maintaining accurate knowledge structures.
• Collaborate with developers, data engineers, AI teams, and business stakeholders on knowledge management projects.
• Manage and update ontologies as new products, services, and business information are introduced.
• Support knowledge graph and metadata initiatives to improve data quality and consistency.
• Use graph databases and ontology management tools (where applicable) to maintain semantic data models.

Ideal Candidate

• Strong Ontologist Profile with deep semantic (RDF) ontology experience in complex enterprise environments
• Mandatory (Experience 1) – Must have 7+ years of total experience, with 5+ years in semantic (RDF) ontology building/structuring for a complex/large enterprises
• Mandatory (Experience 2) – Must have a strong understanding of content and information management, data structures, and semantic metadata extraction
• Mandatory (Tech skill 1) – Must have strong experience with graph databases, taxonomies, and NLP strategies for optimization
• Mandatory (Tech skill 2) – Must have strong working experience of ontology/TOMS tools such as PoolParty (Semantic Web), TopQuadrant EDG, or GraphDB (Ontotext)
• Mandatory (Tech skill 3) – Must be familiar with W3C industry standards, including SPARQL and OWL.
• Mandatory (Communication) – Must be fluent in English, with strong stakeholder management skills to operate across a complex, multi-team environment.many stakeholders.
• Mandatory (Note) – Must be available to work during US time zones for at least 4 hours per day
• Preferred (Education) – Must have a degree in Computer Science or Library Science, preferably with a minor / concentration / certificate in Information Management or Library Automation
• Preferred (Tech skill 3) – Understanding of content development and search/retrieval tools.

🔹 Key Responsibilities

• Design, develop, and deploy production-grade AI/ML and Generative AI solutions

• Work on GEO, AEO, and SGE initiatives to improve visibility across AI-driven search platforms

• Optimize content and digital experiences for conversational queries and LLM-based search

• Develop solutions using LLMs, NLP, embeddings, semantic search, RAG, and vector databases

• Analyze search intent, AI-generated responses, citations, retrieval patterns, and content discoverability

• Build frameworks to measure GEO/AEO strategies and AI-search performance

• Collaborate with Product, Engineering, Content, SEO, Marketing, and Business teams

• Improve solution accuracy, relevance, latency, and user experience

🔹 Mandatory Requirements

✅ 1–4 years of professional experience

✅ Minimum 1 year of hands-on experience in GEO, AEO, or SGE

✅ Experience with prompt engineering, embeddings, vector search, or RAG systems

✅ Understanding of semantic search and entity-based optimization

✅ Exposure to ChatGPT, Google Gemini, or similar LLM platforms

✅ Knowledge of schema, context building, content structuring, and knowledge representation

🎓 Preferred Education

B.Tech, M.Tech, Integrated M.Sc., or MS from a Tier-1 engineering institute such as IIT, NIT, BITS, VIT, DTU, or NSUT.

Company: ContexQ

Location: Singapore / India / Malaysia (Remote/Hybrid)

At ContexQ, we are fundamentally reshaping the emerging landscape of Contextual Decision Intelligence. We leverage cutting-edge composite AI, Vector Search, and advanced graph technology to resolve billions of entities continuously. By uncovering hidden relationships, we revolutionize how global enterprises handle fraud detection, financial crime (AML), risk management, and supply chain intelligence.

We are an ambitious, fast-moving startup taking on massive enterprise big data challenges, and we are looking for a Founding Knowledge Graph Scientist to push the boundaries of what is possible in semantic data resolution and network graph AI.

This is not a traditional corporate research role. We are looking for an elite AI researcher and practitioner with a PhD and the DNA of an entrepreneur—someone who can architect novel Graph Transformer architectures, develop cutting-edge explainable AI (XAI) models for fraud detection, and translate deep academic expertise into high-impact enterprise solutions. You will be at the forefront of designing the intelligence engine that protects global financial institutions from complex, coordinated financial crimes.

THE MISSION

As our Founding Knowledge Graph Scientist, you are the intellectual and technical force behind our core AI reasoning engine. You will bridge the gap between state-of-the-art academic research in graph neural networks and the practical, high-throughput demands of enterprise anti-money laundering (AML) and fraud detection systems.

Your ultimate metric is the accuracy, efficiency, and explainability of our graph-based AI models. You will architect proprietary knowledge graph structures, implement advanced Graph Transformer models (like FraudGT or similar architectures), and create the analytical "awe factor" that proves to C-suite banking executives that ContexQ can catch financial crime that legacy systems miss.

WHAT YOU WILL DO

• Architect the Graph: Design and optimize large-scale financial knowledge graphs that capture complex temporal, spatial, and transactional relationships across billions of nodes and edges to detect collusion and laundering behaviors.

• Pioneer AI Models: Develop, train, and deploy advanced Graph Neural Networks (GNNs) and Graph Transformers specifically tailored for highly imbalanced, large-scale financial data.

• Drive XAI in FinCrime: Champion model transparency by building explainable AI mechanisms that allow compliance officers to understand exactly why a transaction or entity was flagged, ensuring strict adherence to global banking regulations.

• Bridge Research & Product: Act as the crucial link between theoretical AI research and our core product roadmap. Publish findings, stay ahead of state-of-the-art fraud detection methodologies, and directly implement these breakthroughs into the ContexQ platform.

• Collaborate Across Teams: Work seamlessly with Data Engineering, MLOps, and Business Analysts to ensure your graph models are deployed efficiently, scale securely, and directly address the pain points of our enterprise clients.

WHO YOU ARE

• The Deep Expert: You hold a PhD in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or a closely related field, with a heavy research focus on Knowledge Graphs, Graph Neural Networks, or Graph Transformers.

• Domain Specialized: You possess deep expertise (either academic or applied) in utilizing graph analytics for anomaly detection, specifically within the realms of Financial Crime, Fraud detection, or cybersecurity.

• A Proven Builder: You have a track record of translating complex AI theory into functional code (PyTorch, PyTorch Geometric, DGL). You are not just a theoretician; you can build, test, and optimize models for real-world deployment.

• A Master Communicator: You can distill complex mathematical concepts and graph topologies into clear, compelling narratives for both highly technical engineering teams and non-technical business stakeholders.

COMPENSATION & THE CONTEXQ UPSIDE

We are explicitly looking for top-tier research and engineering talent who wants to bet on themselves, act as true owners, and build foundational technology.

We structure compensation to heavily reward dedication, innovation, and long-term impact. In exchange for your deep expertise and technical leadership, we offer competitive compensation, significant early-stage foundational equity worth up to $1,000,000 USD over time, a high-impact remote-first culture, and a structure designed to directly align your wealth creation with the platform's enterprise valuation.

This role is designed for an AI pioneer who wants real skin in the game. If you are looking for a purely academic sandbox with no commercial pressure, this isn't for you. If you want the massive upside of building an enterprise AI juggernaut from the ground up and sharing directly in the value you create by stopping global financial crime, you belong at ContexQ.

🚨 Hiring – Data Scientist | Python + Agentic AI

💼 Experience: 5+ Years

Must Have:

• Strong Data Science experience

• Python

• Agentic AI / AI Agents

• Generative AI / LLMs

• RAG / Vector Databases

• LangChain / LangGraph or similar Agent Frameworks

• Machine Learning & NLP