Intelligent Automation Developer (For independent contractors)

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 experience. CS, Engineering or similar university background is a MUST HAVE. Building products grade GenAI Apps with embedded AI using LLMs, Fine-tuning, deployment, maintenance, observe, improve : MUST-HAVE skills include: Generative 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 MUST. Exposure to Advanced usage in Claude code, cursor, codex or similar IDEs. Proficiency in core Python libraries, Solid understanding of packaging, virtual environments, dependency management, and testing. Familiarity with Pods, Deployments, Services, ConfigMaps/Secrets, basic resource configuration, and debugging.

Practical experience using Airflow as a scheduler for data workflows is a MUST. Ability to design, implement, and maintain DAGs, operators, sensors, and connections; manage retries, SLAs, and backfills. Experience 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 have.

Experience with VAULT, PASSPORT, Gitlab for UAM / Config Management. Exposure to Terraform code for deploying AWS services is good to have. 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.

Offered: Contributing to a high scale, complex, world-renowned product and seeing real-time impact of your work. Working in a fast-paced and performance-driven culture. Career advancement via online and on-the-job training, Hackathons, conferences and active community participation.