AI engineer

Requirements and responsibilities

AI Engineer — Role Overview

We're looking for an AI Engineer who is, first and foremost, a strong software engineer — someone with real backend fundamentals who then uses AI agents, LLMs, and tools like Claude as a force multiplier for full-stack, AI-assisted development. We are still software engineers. AI accelerates how we build; it does not replace knowing how to build.

The wrong candidate is an "AI-only" profile who can prompt but can't reason about a data model, a transaction boundary, or a race condition. The right candidate could hold their own on the engineering team without AI in the room — and is exceptional with it, shipping across the full stack faster than a traditional workflow allows.

You'll work on a modern hospitality platform: a NestJS / TypeScript API backed by MariaDB, with a React / TypeScript frontend, built with a database-first architecture and heavy use of AI-assisted development workflows.

What Makes the Ideal Candidate

Strong software engineer with backend depth (the core requirement). Solid command of fundamentals — API design, service architecture, layered/clean design (controller service repository), separation of concerns, concurrency, error handling, testing, and performance. Writes production-grade code that is correct, maintainable, and holds up under change. This is the non-negotiable foundation everything else sits on.

Real database competence. Comfortable with schema design, query optimization, transactions and isolation levels, indexing, stored procedures, and data modeling. Understands why a query is slow or a write is unsafe — not just how to make the error disappear.

Fluent in full-stack, AI-assisted development. On top of strong engineering, knows how to drive agentic workflows with Claude and LLMs across the whole stack — backend, frontend, and data layer. Decomposes work, orchestrates tools, structures context, and validates output. Picks the right model and pattern for the job, and knows where AI genuinely helps versus where it introduces risk — while always owning the correctness of what ships.

Deeply curious about what happens behind the scenes (the differentiator). Doesn't stop at "it works." Wants to understand the mechanics on both sides — how the runtime, framework, ORM/driver, and data layer actually behave underneath the abstractions, and how tokens, context windows, tool-calling, retrieval, and model behavior work under the hood. This is what separates an engineer who can fix a system from one who can only use it. We value the why over the that.

Strong debugging instincts. Given a failure, a stack trace, or "it works locally but not in prod," reproduces, isolates, and diagnoses methodically — forming hypotheses and following evidence to root cause instead of guessing.

Genuinely eager to learn. The landscape shifts monthly. Stays curious, absorbs new tools and techniques quickly, and treats unfamiliar problems as a chance to level up.

Responsibilities

• Design, build, and maintain features across the full stack — NestJS / TypeScript on the backend, React / TypeScript on the frontend — following the project's layered architecture and quality standards.
• Model and query data in MariaDB — schemas, migrations, stored procedures, and performant, safe queries.
• Use AI agents and Claude to accelerate delivery: scaffolding, refactoring, test generation, and code review — while owning the correctness of everything that ships.
• Debug and root-cause issues end to end, from the frontend and API down to the data layer and the AI-assisted workflows themselves.
• Write tests and uphold quality gates so features are correct and maintainable, not just "done."
• Review code (yours, teammates', and AI-generated) with an engineer's eye for architecture, safety, and data integrity.
• Continuously improve how the team leverages AI tooling — without ever lowering the engineering bar.

Required

• Strong software engineering fundamentals with solid backend experience (Node.js / TypeScript preferred; NestJS a plus).
• Solid relational database skills — SQL, schema design, transactions, indexing, query optimization (MariaDB / MySQL a plus).
• Hands-on experience using AI coding tools / agents (Claude, LLM-based assistants) in a real, full-stack workflow.
• Genuine debugging ability — methodical reproduction, isolation, and root-cause analysis.
• Real interest in understanding the concepts underneath the tools, not just the tools themselves.
• Curiosity and a fast, self-driven learning habit.

Nice to Have

• Experience with agentic / multi-agent orchestration, tool-calling, RAG, or LLM output validation.
• Frontend depth with React / TypeScript.
• Experience with database-first architectures and stored-procedure-heavy systems.
• Awareness of prompt/context engineering and model-selection trade-offs (cost, latency, capability).
• Experience modernizing or migrating legacy systems.

In Short

A strong full-stack software engineer who thinks in clean architecture, reasons about data like a DBA, debugs like a detective, and leverages AI and agents as a power tool for full-stack delivery — someone who always understands why things work under the hood, never just that they do.