Senior AI Engineer (Cloud Architecture Concentration)

Company: Risepoint

Location: Remote (Remote)

Type: Full-time

Level: Senior

Remote: Yes

Posted: 2026-03-06

About this role

Risepoint is an education technology company that provides world-class support and trusted expertise to more than 100 universities and colleges. We primarily work with regional universities, helping them develop and grow their high-ROI, workforce-focused online degree programs in critical areas such as nursing, teaching, business, and public service. Risepoint is dedicated to increasing access to affordable education so that more students, especially working adults, can improve their careers and meet employer and community needs.

The Impact You Will Make

Risepoint is developing an AI-powered Student Journey Platform and is seeking a Senior AI Engineer with deep experience building and operating AI systems at enterprise scale. This role focuses on designing, deploying, and scaling production-grade AI services in cloud environments, with particular emphasis on distributed systems, event-driven architecture, orchestration layers, and Kubernetes-based workloads. The ideal candidate has experience integrating AI capabilities into resilient, high-availability systems that support real-world enterprise traffic and operational demands. This role contributes directly to a platform that is central to the organization’s long-term strategy.

How You Will Bring Our Mission to Life

What You Will Do

  • Design and implement scalable AI service architectures in cloud environments (Azure preferred; AWS or GCP acceptable)
  • Build event-driven systems using queues and messaging platforms (e.g., Azure Service Bus, RabbitMQ, SQS) to support asynchronous AI workloads.
  • Implement event streaming and real-time processing pipelines (e.g., Kafka, Azure Event Hubs, Pub/Sub, Kinesis).
  • Architect , maintain , and scale containerized AI services deployed to Kubernetes, with emphasis on Azure Kubernetes Service (AKS).
  • Design orchestration layers that manage model calls, downstream services, retries, rate limits, and failure handling.
  • Optimize system performance un...

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