AI Engineer

Job description

⭐ **Who we are** Lodgify is a fast-growing scale-up company leading the vacation rental industry. Backed by $30M in funding, our platform empowers property owners and managers worldwide to efficiently manage and grow their business through technology. Headquartered in sunny Barcelona, we're now a team of 380+ people representing over 60 nationalities, united by a passion for transforming the future of short-term rentals. **⭐ Role Overview** We are seeking an AI Engineer specializing in LLMs to help build, evaluate, and ship production-grade generative AI systems. In this role, you will independently deliver LLM features, from prototype to production, applying solid engineering and evaluation practices, and growing toward end-to-end ownership of larger, more ambiguous problems. ### ⭐ How will you make an impact? - Build and ship LLM-powered application features (chatbots, copilots, agents, internal tools), combining components like RAG pipelines, agents, and APIs. - Run and extend LLM evaluations (evals) for the systems you build, using and improving existing gold-standard datasets and benchmarks, implementing automated eval checks and scoring, and applying defined metrics for factuality, grounding, robustness, and user impact. - Diagnose and resolve failure modes (hallucinations, retrieval issues, tool-use errors). - Apply advanced prompt engineering techniques and follow prompt versioning and lifecycle practices. - Incorporate latency, cost, and reliability in your implementation choices, and consider production trade-offs. - Collaborate cross-functionally with engineers, product, data, and design to deliver the right solutions. - Follow established practices for responsible AI, including safety, PII handling, and observability. ### ⭐ What makes you a great fit? - 3+ years of experience in software engineering, machine learning, or applied AI, with a track record of delivering features to completion. - Solid software engineering fundamentals (testing, modular design) in Python. - Experience taking AI or LLM-powered features from concept through deployment, and contributing to their ongoing maintenance. - Familiarity with automated testing strategies for non-deterministic systems, and sound debugging and analytical skills for investigating ambiguous model behavior. - A working understanding of prompt engineering and prompt lifecycle management, RAG architectures and retrieval evaluation, and common LLM limitations and failure patterns. - Experience using Data Analytics techniques (SQL, analysis, and visualization) to inform product decisions and delivery. - A product mindset and a genuine interest in understanding our product and customer needs to build the right solutions. - The ability to independently drive work to completion, and to know when to seek guidance on ambiguity. - Clear communication of trade-offs, risks, and system performance, including the uncertainty inherent in AI systems, to your team and stakeholders. ### ⭐ How can you earn extra bonus points? - Experience contributing to ambiguous projects and communicating technical risks to stakeholders. - Exposure to production-grade evaluation using more advanced metrics and statistical validation. - Hands-on experience with model fine-tuning, adversarial red-teaming, or safety testing.