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Mid-level generalist MLOps role with broad skillset and 3–5 year range increases competition.
MLOps and cloud skills are transferable, but healthcare domain and Azure specifics increase bias.
Explicit 3–5 year requirement plus mandatory tech stack and MLOps experience create moderate filtering.
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Design, build, deploy, and support secure, scalable, cloud-native backend microservices, REST APIs, and AI-enabled applications using C#, .NET, and Python.
Develop and maintain automated CI/CD pipelines incorporating quality, security, and production readiness controls for AI/ML model lifecycle and MLOps workflows.
Implement monitoring and observability (logs, metrics, alerts) for applications and AI models and collaborate cross-functionally to ensure reliable AI-enabled solution deployments.
Bachelor's degree in Computer Science or related field, or equivalent experience.
3–5 years of professional software engineering experience.
Strong programming skills in one or more: C#, .NET, or Python.
Experience with microservices architecture, REST APIs, cloud-native applications, relational databases, data modeling, and query optimization.
Experienced with AI/ML concepts and model lifecycle or MLOps practices to help move AI-enabled solutions from design to production.
Comfortable working in Agile/Scrum environments with cross-functional teams including architecture, product, security, platform, and operations.
Adept at writing clean, maintainable code with strong debugging and problem-solving skills to improve platform reliability through automation and collaboration.