Generative AI Engineer

Booking.com — Netherlands · Posted ~3 hours ago

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Skills

Generative AI AI Applications Software Engineering

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Summary ✨ AI‑Generated

An international technology organization is looking for a Generative AI Engineer to create automation solutions and AI applications. The role requires strong engineering skills, ownership, collaboration, and experience building practical AI products.

Highlights

Opportunity to build AI-powered automation solutions, work cross-functionally, and solve real-world technology challenges.

Description

We are looking for an enthusiastic GENAI Engineer professional to join the ranks of our Intelligent Automation Team to help us meet increasing demand from the business, support our rapidly growing portfolio of automation and make an impact across every business area at Booking.com. We look at our team as a service provider for the entire company, operating with a large degree of autonomy and enterpreneurship. Responsible Naturally oriented towards improving efficiencies.Seeking accountability from themselves and others.Compassionate collaborator with a deep sense of comradery.Willingness to be cross-functional, pick up new skills and cover new ground with/for the team.Striving for continuous improvement and high quality in their work.Strong work ethic and high spirit.Keen to understand and solve real world problems through technology. Skilled Minimum of 5-7 years of experienceCS, Engineering or similar university background is a MUST HAVEBuilding products grade GenAI Apps with embedded AI using LLMs, Fine-tuning, deployment, maintenance, observe, improve : MUST-HAVE skills includeGenerative AI & LLMs: LLM Application Development, Agentic Workflows, RAG Pipelines, Vector Search, Prompt Engineering, LLM Evaluation, Vertex AI, OpenAI API, LangChain/LangGraph, Embeddings.Machine Learning: XGBoost, LightGBM, Scikit-learn, Supervised & Unsupervised Learning, Anomaly & Fraud Detection, Feature Engineering, Model Calibration, Imbalanced Learning, A/B Testing, Causal Inference, Hypothesis Testing.MLOps & Production ML: MLflow, Model Registry, Experiment Tracking, Drift & Performance Monitoring, CI/CD for ML, Reproducible Pipelines, Feature Stores, Model Serving, Shadow Deployments.Data Engineering: Apache Airflow, PySpark, BigQuery, Advanced SQL (Window Functions, CTEs, Query Optimization), ETL/ELT, Streaming & Batch Pipelines, Data Modeling, Analytics Engineering, RESTful APIs.Cloud & Infrastructure: AWS (S3, RDS), Docker, Kubernetes (basics), Git/GitHub Actions, Microservices.Exposure to tools like HoneyComb and Arize is a MUSTExposure to Advanced usage in Claude code, cursor, codex or similar IDEsProficiency in core Python libraries,Solid understanding of packaging, virtual environments, dependency management, and testingFamiliarity with Pods, Deployments, Services, ConfigMaps/Secrets, basic resource configuration, and debugging.Practical experience using Airflow as a scheduler for data workflows is a MUSTAbility to design, implement, and maintain DAGs, operators, sensors, and connections; manage retries, SLAs, and backfillsExperience working with Snowflake (queries, views, warehouses, roles).Strong SQL skills and understanding of performance optimization (clustering, micro-partitions, caching basics)In-depth understanding of AWS components RDS, EC2, S3, IAM, CloudWatch, Lambda,Sagemaker, VPC is good to haveExperience with VAULT, PASSPORT, Gitlab for UAM / Config ManagementExposure to Terraform code for deploying AWS services is good to haveProfessional experience with SQL, .NET, C#, HTTP APIs and Web ServicesExperience designing, developing, deploying and maintaining softwareExperience working in a scrum/agile environmentExcellent communication skills in English Offered Contributing to a high scale, complex, world-renowned product and seeing real-time impact of your workWorking in a fast-paced and performance-driven cultureCareer advancement via online and on-the-job training, Hackathons, conferences and active community participation