Senior AI Engineer, Big Data & AI Solutions

What you'll do

• Build and enhance large-scale data and feature pipelines using Apache Spark, PySpark, Python, and SQL.
• Transform high-volume data into reliable features and inputs to support machine learning models.
• Support model development, evaluation, deployment, and production performance in partnership with data scientists.
• Strengthen model monitoring, observability, and drift detection to identify performance changes.
• Support the ongoing optimization and retraining of production models and their supporting pipelines.
• Apply CI/CD, automated testing, version control, and MLOps practices to improve system reliability and scalability.
• Develop AI-powered solutions, including Generative AI and agentic approaches, to improve engineering workflows.

What we're looking for

• Master’s degree with 2+ years of relevant experience, or Bachelor’s degree with 5+ years of relevant experience, in a related field.
• Hands-on professional experience with Apache Spark/PySpark in large-scale or distributed data-processing environments.
• Hands-on experience with CI/CD practices, including automated integration, testing, or deployment workflows.
• Proficiency with Python and SQL and experience building ETL, data, or feature engineering pipelines.
• Experience working with large-scale data and technologies such as Databricks, Airflow, Hadoop, Linux/Unix, or comparable platforms.
• Understanding of the production machine learning lifecycle, including model development, deployment, monitoring, evaluation, and optimization.
• Experience supporting production AI/ML systems, including model monitoring, observability, or drift detection (preferred).
• Experience in fraud, cybersecurity, payments, risk management, or with Generative AI, LLMs, RAG, or agentic AI (preferred).