[Remote] Principal AI Engineer

Note: The job is a remote job and is open to candidates in USA. Risepoint is an education technology company that provides support to universities and colleges, focusing on developing online degree programs. They are seeking a Principal AI Engineer to lead the technical direction for their Student Journey Platform, which involves architecture design for cloud-native infrastructure, ensuring scalability and reliability, and establishing architecture standards for engineering teams.

Responsibilities

• Lead the architecture and evolution of cloud-native infrastructure for the Student Journey Platform, including all services and its integrated platforms (Salesforce, DBX, Marketing sites, Azure AI Foundry), setting technical direction across Kubernetes-based AI services deployed on Azure (AKS), with accountability for platform-wide scalability, reliability, and cost efficiency
• Establish and promote architecture standards within the platform scope, design patterns, and deployment best practices that all engineering teams build against including service mesh configuration, autoscaling policy design, resource governance, API contracts, and container orchestration strategy
• Lead architecture design and implementation across the platform’s components for SJP, Student Success Team, Marketing Technology, and Enterprise Data Platform implementing a variety of resources (Kafka, Azure Event Hubs, Azure Service Bus, AI Foundry), ensuring asynchronous AI workloads are resilient, observable, and operate without bottlenecks, vulnerabilities, or data loss under production conditions
• Align platform architecture to business growth needs and scalability requirements, partnering with Product, Engineering, and business stakeholders to ensure infrastructure decisions stay ahead of adoption curves not reactive to them
• Present sound architecture proposals to the Architecture Review Board (ARB) for approval of products intended for release into production, representing the Student Journey Platform’s technical strategy as well as its integrated products and services, ensuring alignment with Risepoint’s enterprise standards for SLAs, security, compliance, and scalability
• Identify and resolve architectural risk early, before it compounds, working across engineering teams to close gaps in design, security posture, or operational readiness
• Debug and resolve production-level issues where infrastructure or architecture is a contributing factor, driving root cause resolution rather than symptomatic fixes
• Implement and manage event streaming and real-time processing pipelines (e.g., Kafka, Azure Event Hubs, Pub/Sub, Kinesis) at production scale, supporting high-volume asynchronous AI workloads
• Design and manage multi-tenant cloud infrastructure across university partner deployments, each with potentially distinct compliance, data isolation, and availability requirements

Skills

• 8+ years of software engineering experience with demonstrated progression into architecture ownership including hands-on experience with Kubernetes (AKS preferred), containerization (Docker), and distributed system design at production scale
• A track record of setting technical direction across engineering teams, not just executing within one: including defining standards others build against and influencing architectural decisions in cross-functional environments
• Deep experience with autoscaling policy design, resource governance, and cost management in cloud environments (Azure preferred; AWS or GCP acceptable), managed through infrastructure as code
• Experience translating business and product requirements into infrastructure architecture including capacity planning, SLA definition, and trade-off communication to non-technical stakeholders
• Proficiency in Python, C#, Java, or a comparable language used in production systems, with strong fundamentals in object-oriented programming and design patterns
• Architecture or deployment experience with AI/ML systems in cloud environments. Managed integrations with Databricks model serving endpoints and vector stores a plus
• Implementation experience with Azure AI Foundry and realtime models
• Experience designing APIs and backend systems supporting high concurrency and real-time interactions
• Familiarity with RAG systems, vector stores, and MCP server architecture

Company Overview

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