AI Engineer, Booking.com

• Experience: 4-8 years of professional experience in AI engineering, MLOps, and AI application development
• AI Application Development: Proven experience building and deploying AI applications—from prototype to production—using containerization (e.g., Docker)
• Programming Skills: Fluent in Python and SQL, with working knowledge of TypeScript or JavaScript
• Generative AI Expertise: Strong understanding of AI agent architectures, LLM fine-tuning, prompt engineering, function calling, Retrieval-Augmented Generation (RAG), and LLM orchestration
• Agentic Frameworks: Hands-on experience with LangChain, and familiarity with advanced agentic orchestration frameworks such as LangGraph and CrewAI
• Software & Deployment: Experience with CI/CD pipelines, model versioning, and scalable deployment of AI services
• Cloud Environments: Proficiency in working with cloud platforms (AWS, Azure, or GCP) and integrating GenAI applications with enterprise systems
• Statistical and Data Modeling: Solid understanding of regression, clustering, NLP, and generative modeling (LLMs, transformers)
• Data Management: Skilled in SQL and data wrangling tools for preparing and transforming both structured and unstructured data
• Innovation Mindset: Ability to design and implement innovative GenAI solutions leveraging RAG and LLM integration
• Collaboration: Experience in collaborating with outsourced or third-party technology partners
• Ability to have a good grasp of the detail and manage multiple priorities in a quick turnaround environment
• Strong communication skills in English, both verbal and written
• Organized, flexible, proactive, and result-oriented

Desirable

• We are seeking an AI Engineer to join the team, responsible for co-developing and technically steering an advanced AI-driven platform designed to enable data-driven procurement decision-making
• The solution will be developed in collaboration with a third-party technology partner, while Booking.com retains ownership of the technical direction, integration architecture, and data governance
• You will act as the internal technical lead, ensuring smooth integration of the vendor’s AI solution with Booking.com’s procurement ecosystem (Ivalua, Conga, ORO, …)
• Your focus will be on defining system architecture, data models, and API integrations, validating vendor deliverables, and implementing Booking-specific extensions
• This is a hands-on, technically oriented role that combines AI engineering expertise with the ability to oversee external development work
• Due to the rapid and continuous growth of the organization, the tasks and duties of this role may evolve over time. You will be keen to develop and grow within the role and to take on additional challenges and responsibilities as they occur
• Act as the internal technical lead for the AI-based Category Strategy Optimizer platform, developed in collaboration with a third-party vendor
• Validate the overall architecture, ensuring alignment between Booking.com’s systems (e.g., Ivalua, Conga, ORO) and the vendor’s solution components
• Oversee and technically steer the vendor’s development activities, ensuring code quality, compliance, and performance standards are met
• Collaborate with Procurement, Legal, Finance, and Technology teams to translate business and functional requirements into scalable technical solutions and ensure ongoing compliance with internal security, privacy, and AI governance frameworks
• Review and validate vendor deliverables, including data models, APIs, and AI-driven modules, ensuring adherence to Booking.com’s security and architecture standards
• Develop integration scripts, validation routines, and Booking-specific extensions to enhance functionality and ensure end-to-end system coherence
• Partner with data and platform engineering teams to guarantee robust data flows, pipelines, and governance
• Support implementation of CI/CD automation, monitoring, and model deployment in cloud environments (AWS / GCP)
• Provide technical documentation and training materials, supporting operational readiness and knowledge transfer
• Identify opportunities for optimization, performance improvement, and functional enhancement in collaboration with the vendor and internal stakeholders