Skip to content
- Confident English communication at all levels — developer through to C-suite and client board.
- Demonstrated independent stakeholder management across full project lifecycles.
- Translates LLM/AI complexity into concrete business value for non-technical audiences.
- Surfaces issues early with proposed solutions — proactive by default.
- Disciplined async communicator comfortable in distributed, remote-first environments.
- 4–8 years in software engineering; minimum 2 years in AI/LLM engineering built on a web development foundation.
- Python for AI/ML; JavaScript/TypeScript for web-integrated AI features.
- LLM fundamentals: tokenisation, context windows, RAG, embeddings, fine-tuning concepts.
- Vector databases for semantic search: Pinecone,Weaviate,pgvector, or equivalent.
- AI orchestration frameworks:LangChain,LlamaIndex, or comparable.
- Web architecture literacy: REST APIs, headless CMS, SPA/SSR — sufficient to integrate AI end-to-end.
- DevOps/MLOps: containerisation, CI/CD, model versioning, automated evaluation pipelines.
