B
Booking.com
AI Backend Software Engineer (AI Application Platform)
Skills
Google Cloud PlatformDockerPythonJavaMySQLRedisMachine LearningAIScalaAWSKubernetes
2 months ago
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Important information
Contract type:
Permanent
Location:
Amsterdam, Netherlands
Work mode:
Onsite
Published on:
7 August 2026
What they need
- As a Software Engineer working on the AI Application Platform, you will work at the intersection of scalable backend systems and cutting-edge AI
- You will have the opportunity to design and build the core platform that enables product teams to rapidly develop and deploy AI-powered experiences for millions of people
- You will tackle complex performance and scaling challenges, shape the foundation of our AI infrastructure, and collaborate closely with ML engineers, data engineers, and data scientists to bring intelligent systems into production at scale
- Design and evaluate architecture solutions for AI infrastructure, rapidly prototyping to validate key assumptions and guide decision-making
- Explore, benchmark, and integrate new AI/ML tools and technologies to drive innovative engineering solutions that meet evolving business needs
- Build and maintain scalable, reusable backend services that support real-time AI/ML inference, model deployment, and data pipelines
- Collaborate closely with ML engineers, data engineers, and data scientists to bring AI/ML models into production and optimize system performance
- Take end-to-end ownership of system reliability and operational excellence, including performance tuning, observability and incident management
- Continuously grow technical and interpersonal skills through hands-on experience, knowledge sharing sessions, and industry events
Benefits
- Health insurance
- Free access to Headspace for you and your loved ones
- Global Employee Assistance Program
- Meditation and Breastfeeding rooms at the office
- Booking Cares - 2 days per year to volunteer and learn
- Life insurance
- Disability insurance
- Pension plan
- Annual paid time off
- Parental leave - 22 weeks
- Grandparent leave - 10 days
- Care leave - 10 days
- Bereavement leave - up to 4 weeks
- Anniversary leave
- Working from Home Furniture and Ergonomic Support
- Working from Abroad - up to 20 days per year
- Discounts & Wallet credits to spend on our products
- Upgrade to Booking.com Genius Level 3
- Friends & Family Booking.com discount vouchers
- Free access to online learning platforms
- Development and mentorship programs to support career growth
- Access to trainings and workshops
- Team development opportunities
- Local discount programs
- Game rooms in offices
- On-site meals, coffee and snacks including vegan options- We are looking for driven Software Engineers who enjoy solving problems, who initiate solutions and discussions and who believe that any challenge can be scaled with the right approach and tools
- Experience with containerization tools like Docker and Kubernetes, and deploying applications in cloud environments such as AWS or GCP
- Experience in feature engineering, integrating AI/ML models into production systems, and understanding model behavior, performance and constraints
- Proficiency in one or more server-side programming languages such as Java, Scala, or Python
- Experience working in cross-functional teams alongside ML engineers, data scientists, and product stakeholders to bring AI/ML products to production
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent industry experience
- Experience building AI agents and components such as memory, context engineering, retrieval, and orchestration
- Experience with scalable data storage systems (e.g. MySQL, Redis) and optimizing data access and caching for high-throughput applications
- 3+ years of professional experience in software engineering, with a focus on backend or platform development
- Ability to navigate ambiguity, take ownership of complex problems, and drive them to resolution
- Experience building distributed systems at scale, with a focus on performance tuning, observability, and reliability best practices
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