Applied AI Engineer
Tasks
- Build AI solutions using Azure AI services
- Create reusable prompt and agent design patterns
- Design AI-powered agents and workflows
- Develop AI data pipelines and integrations
- Develop REST APIs and GraphQL APIs
- Evaluate frontier AI techniques with evidence
- Implement AIOps for observability and operations
- Implement DevOps for AI model deployment
- Implement MLOps for training testing monitoring
- Maintain safe fallback behavior for deployed agents
- Monitor model performance and latency
- Support solution lifecycle prototyping testing deployment monitoring
- Test deploy and monitor production AI systems
Perks/Benefits
- N/A
Skills/Tech-stack
AI Foundry | AI Governance | AIOps | Azure AI | Azure AI Foundry | Azure Data | Azure Data Factory | Azure Machine Learning | Azure OpenAI | Azure Synapse | Azure Synapse Analytics | Cognitive Services | Copilot Studio | Data Factory | Data Lake | Delta Lake | DevOps | Docker | ELT | ETL | GDPR | GraphQL | Kubernetes | Lakehouse | MLOps | Machine Learning | Microsoft Fabric | Parquet | Prompt engineering | Python | RAG | REST API | Responsible AI | Retrieval-Augmented Generation | SQL | Synapse Analytics
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Applied AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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