AI Engineer
Role details
Job location
Tech stack
Job description
You will work directly with the founders on client projects, developing AI applications that address operational challenges for our clients. Your responsibilities will include:
- Developing full-stack AI applications using PostgreSQL, Supabase, React, TypeScript, and Python * Implementing RAG systems for enterprise LLM applications * Designing and refining prompt chains and AI agents * Building and integrating internal and external APIs to connect AI systems with existing infrastructure * Benchmarking AI model outputs to ensure reliability and accuracy in regulated environments * Utilising AI coding tools to accelerate development whilst maintaining code quality
You will gain exposure to diverse sectors including legal, healthcare, education, and government, working on projects ranging from rapid internal prototypes to mission-critical production systems., Professional development: You will work directly with two technical founders and other developers, with opportunities for rapid skill development. An annual learning budget supports courses, books, and conference attendance. We support progression towards AI specialisation, technical architecture, or team leadership.
Immediate impact: Contribution to live client projects from the first week, building systems that improve operational efficiency for our clients.
Requirements
Do you have experience in TypeScript?, Do you have a Master's degree?, * Have a demonstrable interest in AI development through side projects, open-source contributions, blog posts, or a GitHub portfolio showcasing AI experimentation * Are comfortable working across the full stack, including databases, APIs, frontends, and AI integration * Have experience with relational databases (PostgreSQL preferred) and API development * Can provide tangible evidence of engagement with AI technologies, whether through weekend LLM projects, prompt engineering experiments, chatbot development, or participation in AI communities, * Experience developing custom RAG systems with vector databases or model fine-tuning * Familiarity with Supabase/SQL or vector databases * Knowledge of prompt engineering techniques (e.g., structured responses, tool use) and understanding of LLM limitations * Experience with AI model evaluation methodologies * Familiarity with automation tools such as N8N