Nice to meet you! We’re a leader in data and AI. Through our software and services, we inspire customers around the world to transform data into intelligence – and questions into answers. If you’re looking for a dynamic, fulfilling career with flexibility and a world -class employee experience, you’ll find it here. We’re recognized around the world for our inclusive, meaningful culture and innovative technologies by organizations like Fast Company, Forbes, Newsweek and more. What you’ll do Looking for that internship? The game-changing one that’ll help you learn, grow, and chart your path forward? You’ll find it at SAS. Our interns aren’t coffee runners – they do real, meaningful work. Our award-winning internship program is focused on development, culture, and community . We’ll help you grow professionally, find (or further) your passion, and make memorable connections that last beyond the summer. AAIM Engineering is part of SAS’s Applied AI and Modeling (AAIM) division, focused on delivering models and agents -as-a- product to customers. Our mission is to transform advanced analytics and AI models into scalable, production-ready solutions that drive real-world impact across industries. We build a repeatable software process for model delivery, ensuring performance, scalability, and quality at every stage. This includes: ModelOps Pipeline Development: Automating the lifecycle from model artifact to containerized product, integrating security scans, validation, and continuous delivery. Infrastructure & Tooling: Providing developers with frameworks, SDKs, and best practices to accelerate deployment and monitoring. Performance & Compliance: Optimizing container runtime, validating KPIs, and ensuring legal, regulatory, and security standards. Innovation & Enablement: Supporting cutting-edge use cases like predictive maintenance, fraud detection, and supply chain optimization through containerized models and REST APIs. In terns at AAIM Engineering work on projects, such as: Building and testing SDKs for model packaging and integration. Enhancing dashboards for operational metrics and performance monitoring. Developing various aspects for Agent ic infrastructure. This is an opportunity to learn ModelOps at scale, gain hands-on experience with cloud-native technologies (Kubernetes, containers, REST APIs), and contribute to solutions that shape the future of applied AI.
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Career Level
Intern
Number of Employees
5,001-10,000 employees