Sr Cloud Applications Engineer
New
J
JobgetherCloud Engineering
United StatesFull-TimeSenior
Salary$104,500 to $136,000 annually
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Job Details
- Experience
- Minimum of 5 years of experience
- Required Skills
- PythonMicrosoft AzureC#.NETLLMMLOps
Requirements
- Bachelor's degree in Computer Science, Software Engineering, or a related technical field (or equivalent practical experience).
- Minimum of 5 years of experience in software engineering or cloud application development, including recent AI/ML implementation experience.
- Hands-on experience building AI and LLM-powered applications using Microsoft Azure AI services, including Azure OpenAI, Azure AI Foundry, and Azure AI Search.
- Experience with retrieval-augmented generation (RAG), prompt engineering, orchestration frameworks, model integration, and evaluation techniques.
- Proficiency with AI-assisted development tools such as GitHub Copilot, Claude Code, or similar coding assistants.
- Strong programming skills in Python, C#/.NET, or comparable languages.
- Experience developing cloud-native applications using Azure services such as App Services, Functions, AKS, containers, API Management, and cloud storage solutions.
- Knowledge of CI/CD pipelines, Infrastructure-as-Code, automated testing, observability, and Agile development practices.
- Familiarity with MLOps and LLMOps principles.
- Understanding of secure application architecture, identity management, API security, and data protection in regulated environments.
Responsibilities
- Design, develop, and deploy cloud-native AI applications using Microsoft Azure services and large language model (LLM) technologies.
- Build AI-powered capabilities such as retrieval-augmented generation (RAG), prompt orchestration, model integrations, and intelligent automation solutions.
- Establish reusable engineering frameworks, governance standards, and development patterns for AI application delivery.
- Collaborate with security and compliance teams to ensure AI solutions meet data privacy, security, and regulatory requirements.
- Serve as the technical lead for AI engineering initiatives, providing architecture guidance and hands-on development support.
- Identify opportunities to improve operational efficiency through internally developed AI tools and automation.
- Partner with business stakeholders to gather requirements and translate them into scalable technical solutions.
- Optimize the performance, reliability, scalability, and cost efficiency of cloud and AI services.
- Recommend improvements to engineering processes, tooling, and cloud architecture.
- Mentor engineers on AI-assisted development practices and promote adoption of modern engineering methodologies.
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