Sr Cloud Applications Engineer
$104,500–$104,500 year
RemoteUnited States
Job Summary
Design and develop AI/LLM-powered capabilities for internal business problems using Azure AI services, including retrieval-augmented generation and orchestration. Establish reusable patterns, frameworks, and guardrails for building AI applications while partnering with Security and Compliance to ensure secure-by-design standards. Serve as the technical point of contact and hands-on developer accelerating AI solution delivery, translating business requirements into scalable cloud-native applications on Microsoft Azure. Monitor service performance, reliability, and cost-effectiveness, and mentor engineers adopting AI-assisted development practices. Collaborate with cross-functional teams to align AI capabilities with organizational goals and recommend improvements to engineering processes.
Required Qualifications
- 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
- Trailhead participation
Desired Qualifications
- Microsoft/Azure AI certifications
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