Senior AI Engineer - Production AI & Agent Systems

Mastercard; Little Canada (MN); On-site; USD 78,000 - 113,000; Full time

Job summary

Mastercard is seeking a Senior AI Engineer to independently design, build, and deploy agent-based systems and developer tooling that scale AI across the enterprise. You will partner with data science to move proofs of concept into production, focusing on reliability, governance, and measurable performance.

You will work with python, SQL, and cloud platforms, building pipelines, and integrating APIs while ensuring robust CI/CD practices and observability across services.

Qualifications

• Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field.
• Hands-on experience building agentic systems in production or near-production settings.
• Proficiency in Python and SQL, with solid software engineering fundamentals.
• Experience with API design, integration, and internal tooling.
• CI/CD and build tooling such as Git, Jenkins, Maven, and Artifactory.
• Experience deploying models or applications to production with monitoring and versioning.
• Working knowledge of cloud environments.

Responsibilities

• Independently execute key elements of projects within AI Engineering and resolve roadblocks.
• Design and build agentic systems and internal tooling, including orchestration and guardrails.
• Collaborate with data science to productionize proofs of concept and deploy them.
• Implement models into production and design scalable training pipelines.
• Monitor model and agent performance and ensure ethical AI practices.

Skills

Python

SQL

Generative AI

LLMs

API design

CI/CD

Cloud platforms

Databricks/Spark

Production deployment

Education

Bachelor's degree in CS/AI/ML

Tools

Git

Jenkins

Maven

Artifactory

LangGraph

LangChain

CrewAI

Job description

Mastercard is seeking a Senior AI Engineer to independently design, build, and deploy agent-based systems and developer tooling that scale AI across the enterprise. You will partner with data science to move proofs of concept into production, focusing on reliability, governance, and measurable performance.

You will work with python, SQL, and cloud platforms, building pipelines, and integrating APIs while ensuring robust CI/CD practices and observability across services.