Software Engineer 2

Role Summary

As a Software Engineer 2 – AI & MLOps, you will design, build, deploy, and support secure, scalable, cloud-native applications and AI-enabled services. You will combine strong software engineering fundamentals with MLOps, automation, observability, and production reliability practices.

Key Responsibilities

• Develop backend microservices, REST APIs, and AI-enabled solutions using C#, .NET, Python.
• Build and support AIOps workflows for deployment, validation, monitoring, and governance.
• Create automated CI/CD pipelines with quality, security, and production-readiness controls.
• Implement application and AI observability through logs, metrics, traces, alerting.
• Collaborate with architecture, data, product, security, platform, and operations teams to deliver reliable solutions.
• Participate in design and code reviews, testing, sprint planning, production support, and continuous improvement.
  
  
  

Required Qualifications

• Bachelor’s degree in Computer Science or a related field, or equivalent experience.
• 3–5 years of professional software engineering experience.
• Strong programming skills in one or more of C#, .NET, or Python.
• Experience with microservices, REST APIs, cloud-native applications, relational databases, data modeling, and query optimization.
• Knowledge of object-oriented design, design patterns, clean code, automated testing, Git, and Agile/Scrum practices.
• Foundational understanding of AI/ML concepts and exposure to model lifecycle or MLOps practices.
• Strong debugging, problem-solving, ownership, communication, and cross-functional collaboration skills.
  
  
  

Preferred Qualifications

• Hands-on experience with Azure, infrastructure as code, or event-driven systems.
• Exposure to Azure AI, Azure Machine Learning, Azure OpenAI, or comparable platforms.
• Familiarity with Application Insights, Azure Monitor, Log Analytics, responsible AI, privacy, and secure development.
  
  
  

What Success Looks Like

You consistently deliver secure, maintainable software; help move AI-enabled solutions from design to production; support reliable model deployment and monitoring; resolve ambiguity and complex issues; and improve platform reliability through automation and collaboration.

Equal Opportunity: Providence is proud to be an Equal Opportunity Employer and values diverse backgrounds, experiences, abilities, and perspectives.

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