Applied AI Engineer
Tasks
- Apply software engineering data engineering and AI best practices for secure scalable maintainable solutions
- Build AI solutions using Azure AI services
- Build and integrate data pipelines APIs and enterprise data sources
- Design AI powered agents and workflows for business challenges
- Develop reusable prompt and agent design patterns for reuse across initiatives
- Evaluate frontier techniques and recommend improvements with evidence
- Implement DevOps MLOps and AIOps for deployment observability and operations
- Implement safe fallback behavior in production agents
- Monitor model behavior and maintain accuracy reliability and latency thresholds
- Support solution lifecycle including prototyping testing deployment monitoring and continuous improvement
Perks/Benefits
- N/A
Skills/Tech-stack
AI Foundry | AI Governance | AIOps | API Development | Azure AI | Azure AI Foundry | Azure Data | Azure Data Factory | Azure Machine Learning | Azure OpenAI | Azure Synapse | Azure Synapse Analytics | Copilot Studio | Data Factory | Data Lakehouse | Delta Lake | DevOps | Docker | ELT | ETL | GDPR | GraphQL | Kubernetes | MLOps | Machine Learning | Microsoft Copilot | Microsoft Copilot Studio | 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
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