Intelligent Automation Developer

at Booking.com

📍 Amsterdam, Netherlands

EUR 30-75 per hour

SENIOR

✅ Hybrid ✅ On-site

✅ Contract / Freelance

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

A/B Testing @ 4 AI @ 4 API @ 4 AWS @ 4 AWS RDS @ 4 Agile @ 4 Airflow @ 4 CI/CD @ 4 Claude Code @ 6 Codex @ 6 Communication @ 6 Data Engineering @ 4 Data Modeling @ 4 Debugging @ 3 Docker @ 4 ELT @ 4 ETL @ 4 Fraud @ 4 GenAI Generative AI @ 4 Git @ 4 GitHub @ 4 GitHub Actions @ 4 HTTP @ 6 Kubernetes @ 4 LLM @ 4 LangChain @ 4 LightGBM @ 4 MLFlow @ 4 MLOps @ 4 Machine Learning @ 4 Microservices @ 4 Observability Performance Monitoring @ 4 Performance Optimization @ 7 Prompt Engineering @ 4 Python @ 6 RAG @ 4 SQL @ 4 Snowflake @ 4 Terraform @ 6 Vault @ 4 Vertex AI @ 4 XGBoost @ 4 scikit-learn @ 4

Details

We are looking for an enthusiastic GenAI Engineer professional to join the Intelligent Automation Team. The team supports increasing business demand, maintains a growing portfolio of automation, and delivers impact across every business area at Booking.com. The team operates as a service provider for the entire company with a high degree of autonomy and entrepreneurship.

Responsibilities

Improve operational efficiencies and solve real-world problems through technology.
Take accountability for individual and team outcomes.
Collaborate compassionately across functions and develop new skills as needed.
Contribute to continuous improvement and high-quality delivery.
Design, develop, deploy, and maintain software and production-grade GenAI applications.
Build GenAI applications using embedded AI, LLMs, fine-tuning, deployment, maintenance, observability, and continuous improvement.
Design, implement, and maintain Airflow DAGs, operators, sensors, and connections.
Manage workflow retries, SLAs, and backfills.
Develop and maintain data workflows, machine-learning pipelines, and software in a Scrum/Agile environment.

Requirements

Minimum of 5–7 years of experience.
A university background in Computer Science, Engineering, or a similar field is required.
Experience with Generative AI and LLMs, including LLM application development, agentic workflows, RAG pipelines, vector search, prompt engineering, LLM evaluation, Vertex AI, OpenAI API, LangChain/LangGraph, and embeddings.
Experience with machine learning, including XGBoost, LightGBM, Scikit-learn, supervised and unsupervised learning, anomaly and fraud detection, feature engineering, model calibration, imbalanced learning, A/B testing, causal inference, and hypothesis testing.
Experience with MLOps and production machine learning, including MLflow, model registries, experiment tracking, drift and performance monitoring, CI/CD for ML, reproducible pipelines, feature stores, model serving, and shadow deployments.
Experience with data engineering technologies and practices, including Apache Airflow, PySpark, BigQuery, advanced SQL, ETL/ELT, streaming and batch pipelines, data modeling, analytics engineering, and RESTful APIs.
Experience with AWS, including S3 and RDS; Docker; Kubernetes basics; Git/GitHub Actions; and microservices.
Exposure to Honeycomb and Arize is required.
Exposure to advanced usage of Claude Code, Cursor, Codex, or similar IDEs.
Proficiency with core Python libraries and a solid understanding of packaging, virtual environments, dependency management, and testing.
Familiarity with Kubernetes pods, deployments, services, ConfigMaps/Secrets, basic resource configuration, and debugging.
Practical experience using Airflow as a scheduler for data workflows is required.
Experience working with Snowflake, including queries, views, warehouses, and roles.
Strong SQL skills and understanding of performance optimization, including clustering, micro-partitions, and caching basics.
In-depth understanding of AWS RDS, EC2, S3, IAM, CloudWatch, Lambda, SageMaker, and VPC is desirable.
Experience with Vault, Passport, and GitLab for user access management and configuration management.
Exposure to Terraform code for deploying AWS services is desirable.
Professional experience with SQL, .NET, C#, HTTP APIs, and web services.
Experience designing, developing, deploying, and maintaining software.
Experience working in a Scrum/Agile environment.
Excellent communication skills in English.

Benefits

Contribute to a high-scale, complex, world-renowned product and see the real-time impact of your work.
Work in a fast-paced and performance-driven culture.
Access career advancement through online and on-the-job training, hackathons, conferences, and active community participation.