> Markdown version of [/jobs/ext/1916501-sr-cloud-applications-engineer](https://www.wearedevelopers.com/jobs/ext/1916501-sr-cloud-applications-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Cloud Applications Engineer - **Company:** HealthEquity Inc. - **Location:** Draper, UT, United States (Remote available) - **Experience:** Expert - **Salary:** $104,500.0 - $136,000.0 - **Contract:** Permanent contract - **Skills:** .NET Framework, Agile Methodology, Artificial Intelligence, Systems Engineering, Automation of Tests, Microsoft Azure, C Sharp (Programming Language), Software as a Service, Cloud Computing, Cloud Engineering, Computer Programming, Continuous Integration, Data as a Services, DevOps, Python (Programming Language), Azure Active Directory, Cloud Services, Azure Machine Learning, Search Technologies, Software Engineering, Systems Integration, Spring Cloud, GitHub Copilot, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Software Security, AI Platforms, Kubernetes, Information Technology, Machine Learning Operations, Api Management - **Published:** August 4, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17808587?backUrl=%2Fcareer%2F17808587%2FSr-Cloud-Applications-Engineer-Utah-Draper ## About the Role * 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. Technical Skills: * 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. Other Skills: * 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. ## Description 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. ## Related Videos - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [This App Reached 10,000 Users in One Week. 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