Note: The job is a remote job and is open to candidates in USA. HealthEquity is focused on empowering healthcare consumers through innovative technology and service delivery. The Senior Cloud Applications Engineer will architect and develop a cloud-native AI engineering platform on Microsoft Azure, building AI/LLM applications and reusable engineering patterns, frameworks, and guardrails. The role also partners with security, compliance, IT, and business teams to deliver secure, scalable, and cost-effective AI solutions from architecture through production.
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
Skills
- 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
Benefits
- Performance-based incentives
- Restricted stock units
- Medical, dental, and vision
- HSA contribution and match
- Dependent care FSA match
- Uncapped paid time off
- Paid parental leave
- 401(k) match
- Personal and healthcare financial literacy programs
- Ongoing education & tuition assistance
- Gym and fitness reimbursement
- Wellness program incentives
- Remote work arrangement
- HealthEquity covers all required travel and accommodations for the onsite Trailhead onboarding session
Company Overview
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