Sr Cloud Applications Engineer

HealthEquity is committed to saving and improving lives by empowering healthcare consumers. The Sr Cloud Applications Engineer will be responsible for designing and building cloud-native applications and AI services on Microsoft Azure, ensuring secure and efficient AI solutions for the organization.

Responsibilities:

• Designing and developing AI/LLM-powered capabilities for internal business problems — including retrieval-augmented generation, orchestration, prompt and model integration — using Azure AI services (Azure OpenAI / Azure AI Foundry, Azure AI Search)
• Using agentic coding assistants (e.g., Claude Code, GitHub Copilot) as part of day-to-day development to accelerate delivery and model best practices for AI-assisted engineering
• Establishing reusable patterns, frameworks, and guardrails for building AI applications — LLMOps/MLOps, evaluation, observability, and cost control — that other IT Engineering teams can adopt
• Partnering with Security and Compliance to ensure all AI and cloud application work is secure-by-design and meets HealthEquity's HIPAA and data-protection standards
• Serving as the technical point of contact and hands-on developer accelerating AI solution delivery across the organization
• Identifying opportunities where internally built AI tools can reduce reliance on third-party software, contributing to operational efficiency
• Contributing to the ongoing infrastructure and architecture of our AI engineering capability as a secure, scalable, cloud-native application on Microsoft Azure
• Collaborating with cross-functional teams (IT, security, and business stakeholders) to ensure our AI capabilities meet business needs and align with organizational goals
• Working with business units to gather requirements and translate them into AI-powered solutions
• Monitoring and optimizing the performance, reliability, and cost-effectiveness of our AI and cloud services
• Providing updates and recommendations to IT Engineering leadership on AI platform direction, adoption, and opportunities for improvement
• Recommending improvements to engineering processes, standards, and tooling to increase the safety and efficiency of AI development across the organization
• Mentoring and supporting other engineers as they adopt AI-assisted development practices and our platform's engineering patterns
• Performing additional duties as assigned or identified to support team objectives

Requirements:

• Bachelor's degree in Computer Science, Software Engineering, or a related technology field, or equivalent practical experience
• Minimum of 5 years of experience in software or cloud application engineering, including recent hands-on AI/ML development
• Hands-on experience building AI/ML and LLM-based applications, including the Azure AI portfolio (Azure OpenAI / Azure AI Foundry, Azure AI Search), retrieval-augmented generation, orchestration frameworks, prompt engineering, and model integration and evaluation
• Hands-on experience using agentic coding assistants (e.g., Claude Code, GitHub Copilot) as part of day-to-day development
• Strong software development skills for cloud-native applications on Microsoft Azure (e.g., App Service, Functions, containers/AKS, API Management, storage and data services)
• Strong programming skills (e.g., Python, C#/.NET) and modern engineering practices: CI/CD, Infrastructure-as-Code, automated testing, and observability
• Familiarity with MLOps/LLMOps and Agile delivery methodologies
• Solid grounding in secure application design, identity (Microsoft Entra ID), API security, and data protection appropriate to a HIPAA-regulated environment
• Architectural judgment — able to evaluate trade-offs (model selection, cost, latency, accuracy, safety) and design sound approaches in an ambiguous, fast-changing domain
• Strong communication and collaboration skills, with the ability to partner across Engineering, Security, Compliance, and business stakeholders
• Microsoft/Azure AI certifications are a plus but not required