AI Engineer

Overview

As a Senior AI Engineer, you will design, evaluate, and deploy production-grade LLM-powered solutions that power chatbots, copilots, and internal tools. You will own end-to-end MLLM initiatives, from prototyping to scalable production, while establishing robust evaluation and responsible-AI practices. You will work closely with product, data, and leadership to shape AI strategy and ensure reliability, latency, and cost targets.

This role offers the opportunity to craft impactful AI features, lead cross-functional efforts, and mentor junior engineers. Join a fast-growing, international team and help transform the way Lodgify delivers AI-enabled experiences.

• remote from home
• 25 days paid vacation
• health insurance (Cigna) with travel and dental
• meal allowance and flexible remuneration
• home-office setup allowance
• free Spanish classes

• Lead the design and development of LLM-powered applications (chatbots, copilots, agents, internal tools).
• Own the LLM evaluation strategy, including gold-standard datasets, automated pipelines, and metrics for factuality, grounding, robustness, and user impact.
• Diagnose and resolve complex failure modes such as hallucinations and retrieval issues.
• Optimize systems for latency, cost, scalability, and reliability in production.
• Mentor junior engineers and promote best practices in LLM development and evaluation.
• Collaborate cross-functionally to shape AI strategy and set standards for responsible AI, safety, bias mitigation, and observability.

• 5+ years of experience in software engineering, machine learning, and applied AI with a track record of delivering projects.
• Strong Python software engineering fundamentals (testing, modular design, dependency injection).
• Experience taking AI/LLM features from concept to production maintenance.
• Automated testing strategies for non-deterministic systems and strong debugging skills.
• Expertise in prompt engineering, prompt lifecycle management, RAG architectures, retrieval evaluation, and LLM limitations.
• Proficiency in data analytics (SQL, analysis, visualizations) to inform product decisions.
• Product-minded with ability to understand customer needs and design appropriate solutions.
• Strong technical leadership, mentorship, and independent project delivery ability.
• Clear communication of trade-offs, risks, and system performance to stakeholders.

• leadership
• mentorship
• cross-functional collaboration
• LLM development and evaluation
• prompt engineering and lifecycle management
• RAG architectures