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AI Engineer
Skills
Computer ScienceAmazon Web ServicesAnalyticsConnectorsDatabasesDriftLarge Language Models
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 2-5 years combined experience in software engineering ML and/or MLOps
- Proven success deploying AI ML models in Microsoft or AWS environments
- Strong proficiency in Python and ML frameworks such as Scikit-learn PyTorch and TensorFlow
- Hands-on experience with Microsoft Copilot Studio Power Automate and Power Apps development
- Experience deploying AI pipelines in AWS SageMaker or Azure ML
- Familiarity with LLM-based copilots agent orchestration and prompt engineering
- Bachelor’s or Master’s degree in Computer Science Data Science or a related technical field
- Must be authorized to work in the United States
Nice to have
- Secure connectors
- RAG architectures
- Azure OpenAI Service
- Dataverse
- Microsoft Graph APIs
- Insurance domain knowledge
Day to day
- Design, develop, deploy, and maintain enterprise-grade AI and machine learning solutions across Microsoft Copilot Studio, Power Platform, and AWS environments.
- Build and operationalize intelligent copilots and AI agents that enhance internal workflows and external customer experiences.
- Automate ML pipelines, manage model lifecycle tasks, and ensure secure scalable integration with business systems.