AI Backend Software Engineer II - AI Application Platform

Booking Booking · Hospitality · Amsterdam, Netherlands · Engineering

Software Engineer on the AI Application Platform team at Booking.com, responsible for designing and building the core platform that enables product teams to rapidly develop and deploy AI-powered experiences. The role involves tackling complex performance and scaling challenges, shaping AI infrastructure, and collaborating with ML engineers, data engineers, and data scientists to bring intelligent systems into production at scale. Key responsibilities include designing architecture solutions for AI infrastructure, integrating new AI/ML tools, building scalable backend services for inference and deployment, and ensuring system reliability and operational excellence.

What you'd actually do

  1. Design and evaluate architecture solutions for AI infrastructure, rapidly prototyping to validate key assumptions and guide decision-making.
  2. Explore, benchmark, and integrate new AI/ML tools and technologies to drive innovative engineering solutions that meet evolving business needs.
  3. Build and maintain scalable, reusable backend services that support real-time AI/ML inference, model deployment, and data pipelines.
  4. Collaborate closely with ML engineers, data engineers, and data scientists to bring AI/ML models into production and optimize system performance.
  5. Take end-to-end ownership of system reliability and operational excellence, including performance tuning, observability and incident management.

Skills

Required

  • 3+ years of professional experience in software engineering, with a focus on backend or platform development.
  • Experience building distributed systems at scale, with a focus on performance tuning, observability, and reliability best practices.
  • Experience with scalable data storage systems (e.g. MySQL, Redis) and optimizing data access and caching for high-throughput applications.
  • Proficiency in one or more server-side programming languages such as Java, Scala, or Python.
  • Experience in feature engineering, integrating AI/ML models into production systems, and understanding model behavior, performance and constraints.
  • Experience building AI agents and components such as memory, context engineering, retrieval, and orchestration.
  • Experience working in cross-functional teams alongside ML engineers, data scientists, and product stakeholders to bring AI/ML products to production.
  • Experience with containerization tools like Docker and Kubernetes, and deploying applications in cloud environments such as AWS or GCP.
  • Ability to navigate ambiguity, take ownership of complex problems, and drive them to resolution.
  • Bachelor's or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent industry experience.

What the JD emphasized

  • Experience building distributed systems at scale
  • Experience building AI agents and components such as memory, context engineering, retrieval, and orchestration.
  • Experience working in cross-functional teams alongside ML engineers, data scientists, and product stakeholders to bring AI/ML products to production.

Other signals

  • AI Application Platform
  • deploy AI-powered experiences
  • intelligent systems into production at scale
  • AI/ML inference
  • model deployment
  • AI/ML models into production
  • AI agents and components