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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer, Big Data & AI Solutions - **Company:** Mastercard - **Location:** O'Fallon, MO, United States - **Experience:** Expert - **Salary:** $115,000.0 - $184,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Automation of Tests, Big Data, Cloud Database, Cyber Security, Continuous Integration, Extract Transform Load (ETL), Linux, Distributed Data Store, Fraud Prevention and Detection, Apache Hadoop, Monitoring of Systems, Python (Programming Language), Machine Learning, Standard Sql, Software Deployment, SQL Databases, Feature Engineering, GitHub Copilot, Retrieval-Augmented Generation, Delivery Pipeline, Large Language Models, Claude Code, Apache Spark, Generative AI, Agentic-AI, Pyspark, Information Technology, Cybercrime, Data Management, Machine Learning Operations, Drift Detection, Software Version Control, Data Pipelines, Databricks - **Published:** October 26, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3468361901&tx=KP6565FFJ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role You are a big data and AI/ML engineer who has used Apache Spark in a professional environment and has hands-on experience working within CI/CD-driven engineering environments., This role requires hands-on professional experience with Apache Spark, Python, CI/CD, and familiarity with AI-assisted development tools. * Master's degree with 2+ years of relevant experience, or Bachelor's degree with 5+ years of relevant experience, in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field; equivalent practical experience will also be considered. * 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 data platforms. * Understanding of the production machine learning lifecycle, including model development, deployment, monitoring, evaluation, and optimization. * Strong problem-solving, communication, and cross-functional collaboration skills. Preferred Qualifications * Experience supporting production AI/ML systems, including model monitoring, observability, or drift detection. * Experience in fraud, cybersecurity, payments, or risk management. * Experience with Generative AI, LLMs, RAG, or agentic AI. * Familiarity with AI-assisted development tools such as GitHub Copilot or Claude Code. * Experience with cloud-based data and AI environments. Technical Environment * Apache Spark / PySpark (required) * Python (required) * CI/CD (required) * SQL * Databricks * Airflow * Hadoop * ETL & Data Pipelines * Feature Engineering * MLOps * Model Monitoring * GenAI / LLMs / RAG / Agentic AI ## Description The Security Solutions Data Science team develops AI and machine learning capabilities that help protect the global payments ecosystem from fraud and cyber threats. Supporting Mastercard's Safety Net product, the team develops and enhances models that analyze billions of transactions and identify suspicious activity., As a Senior AI Engineer, you will work at the intersection of big data engineering and AI/ML, helping build and support the data, features, models, and production processes behind fraud detection., You understand how large-scale data moves from raw inputs through data and feature pipelines into machine learning models, and how those models are deployed, monitored, and improved in production. Large-scale data ? Spark/PySpark ? Data & Feature Pipelines ? ML models ? Production Deployment? CI/CD?Monitoring & Drift Detection ? Optimization & Retraining Experience with Generative AI, RAG, LLMs, or agentic AI is valuable, but the foundation for this role is large-scale data engineering and production AI/ML. What You'll Do Big Data & Feature Engineering * 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 that support machine learning models. Production AI/ML * Partner with Data Scientists and Engineers to support model development, evaluation, deployment, and production performance. * Strengthen model monitoring, observability, and drift detection to identify changes in model or data performance. * Support the ongoing optimization and retraining of production models and their supporting pipelines. MLOps & AI Engineering * Apply CI/CD, automated testing, version control, and MLOps practices to improve reliability and scalability. * Develop AI-powered solutions, including Generative AI and agentic approaches, that improve engineering workflows and operational efficiency., All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: * Abide by Mastercard's security policies and practices; * Ensure the confidentiality and integrity of the information being accessed; * Report any suspected information security violation or breach, and * Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.