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Semantic Architect | Knowledge Graphs | Natural Language Processing | LLM | Ontologies | London, Hybrid
Mission
We are a growing health-technology company building AI systems that improve how information flows within healthcare organisations.
Our platform combines natural language processing, knowledge graphs, and generative AI to help healthcare providers and payers reduce administrative workload, improve decision-making, and deliver better outcomes.
We are now hiring a Semantic Architect to lead the design and implementation of our graph-integrated generative AI architecture.
This is a senior, hands-on technical leadership role focused on building production-grade AI systems that combine LLMs, NLP pipelines, and structured knowledge.
The Role
You will design and own the architecture that connects:
- NLP pipelines processing clinical text
- Knowledge graphs and ontologies
- LLM reasoning and orchestration layers
- Evaluation and benchmarking systems
- Your goal is to ensure these components work together as a coherent, reliable, and explainable AI platform suitable for regulated healthcare environments.
- You’ll also help scale the Applied AI function by setting technical standards and coordinating complex AI development across engineering teams.
Key Responsibilities
Architecture & Technical Leadership
- Design end-to-end AI architectures integrating NLP, LLM orchestration, and knowledge graphs
- Define how structured semantics guide and validate generative outputs
- Set technical design standards for Applied AI systems
- Ensure AI features are robust, production-ready, and aligned with product goals
Applied AI Delivery
- Break product requirements into clear technical implementation plans
- Coordinate work across NLP, graph engineering, and product teams
- Maintain architectural coherence as systems scale
Evaluation & Quality
- Design evaluation frameworks for:
- hallucination detection
- clinical concept extraction accuracy
- model regression testing
- Implement structured outputs and schema-constrained generation
- Introduce human-in-the-loop review and continuous evaluation
Compliance-Aware AI Systems
- Build AI workflows with traceability and auditability by default
- Ensure systems align with healthcare regulatory requirements across UK and US contexts
Requirements
Core Experience
- MSc in Computer Science, AI, or related field (or equivalent experience)
- 3+ years building production AI systems involving structured knowledge
- Strong experience integrating LLMs with knowledge graphs or structured data
- Experience building NLP pipelines and semantic reasoning systems
Technical Skills
- Python for NLP pipelines, orchestration, and evaluation tooling
- Experience with LLM engineering and prompt design using structured outputs
- Familiarity with schema-constrained generation (JSON / ontology-driven outputs)
- Experience designing evaluation frameworks for production LLM systems
Knowledge Graphs
- Experience designing AI systems grounded or validated by graph structures
- Ability to collaborate with knowledge engineers on ontology design
- Understanding of graph performance and scaling considerations
Nice to Have
- Experience in regulated environments (healthcare, fintech, gov, etc.)
- Experience integrating AI systems into production services
- Interest in building reliable AI systems in high-impact domains
What We’re Looking For
- Systems thinker who values clarity and architectural coherence
- Pragmatic engineer focused on production impact
- Comfortable taking ownership of complex technical systems
- Strong communicator who shares and documents architectural knowledge
Hiring Process
- Introductory screening interview (30 mins)
- Technical deep-dive interview with AI and engineering leadership
- Final interview and offer
Benefits
- Competitive salary
- Company pension
- 25 days annual leave
- Flexible hybrid working
- Employee Assistance Programme
- Central London office
Semantic Architect | Knowledge Graphs | Natural Language Processing | LLM | Ontologies | London, Hybrid
