Data and Analytics - AI Engineer II
Tasks
- Apply AIOps MLOps practices
- Build and deploy RAG augmented copilots
- Build production ready AI applications
- Conduct code reviews and documentation
- Contribute to enterprise AI strategy
- Deploy and monitor AI models
- Design AI/ML solutions
- Develop data pipelines for AI workloads
- Ensure AI security compliance and governance
- Implement APIs and services for agent integration
- Implement continuous model improvements
- Integrate agentic workflows into enterprise systems
- Maintain and optimize training and inference pipelines
- Monitor model accuracy drift and performance metrics
- Partner with data IT and business stakeholders
- Promote responsible AI fairness explainability and compliance
Perks/Benefits
- Continuous learning
- Hybrid work environment
- Professional growth
- Supportive collaborative environment
Skills/Tech-stack
AI Foundry | AIOps | Azure | Azure AI | C# | Language Processing | ML.NET | MLOps | Microsoft Power | Microsoft Power Platform | Natural Language | Natural Language Processing | Power Automate | Power Platform | PyTorch | Python | RAG | SQL | SQL Server | Snowflake | TensorFlow
Education
N/A
Roles
AI | AI Engineer | AI Engineer II | Engineer | Engineer II | Learning Engineer | Machine Learning Engineer
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