AI Engineer (AI-Native Development & Claude-based Systems)

Who we are

We are moving towards an AI‑native delivery model where small, highly skilled teams are augmented by AI agents. Instead of relying on traditional, fully manual analysis and specification phases, we use AI to accelerate understanding of existing systems, identify gaps, and generate high‑quality specifications.
As an AI Engineer, you play a key role in building and running the technical backbone that enables this new way of working.

What you’ll be doing

• Implement and maintain the AI backbone that supports end‑to‑end delivery
• Configure, train, and orchestrate AI models and agents working directly on existing codebases
• Enable automated gap analysis, requirement refinement, and specification generation using AI
• Integrate AI capabilities into real-world software systems, not isolated PoCs
• Ensure AI‑driven outputs are robust, scalable, and accurate enough for enterprise use
• Continuously improve prompts, workflows, and agent coordination to increase quality and consistency
• Work closely with the Intent Engineer to iterate on outputs and ensure alignment with business intent
• Support a shift from traditional requirement creation to AI‑assisted, exploration‑driven delivery

What you’ll bring along

• 5+ years of professional experience in software engineering, backend, or platform engineering roles
• Strong software engineering background with hands-on experience in modern architectures
• Experience in the insurance domain, with exposure to insurance platforms, business processes, or core systems (e.g. policies, claims, billing, underwriting, integrations)
• Familiarity with AI‑native engineering practices, such as agent‑based or orchestration‑driven approaches (e.g. Gastown‑style concepts)
• Hands-on experience with Claude or similar large language models, including:
  • Using AI tools directly within an IDE or development workflow
  • Writing effective prompts for code analysis, code generation, and iterative refinement
• Solid understanding of modern engineering patterns, including:
  • API design and integration
  • Microservices architectures
  • Event‑driven and integration‑based systems
• Experience working with existing, non‑trivial codebases and enabling AI‑driven analysis on top of them
• Practical understanding of prompt engineering as an engineering tool, not just experimentation
• A mindset focused on production quality, repeatability, and maintainability rather than demos
• Very good command of English (spoken and written), suitable for working in an international, client‑facing environment