Principle Data Engineer
Tasks
- Architect and deliver AI platforms copilots agentic systems and intelligent applications
- Create reusable AI frameworks SDKs and platform services
- Design and build AI ready data platforms knowledge systems and orchestration frameworks
- Drive technical strategy and architecture for applied AI solutions
- Establish responsible AI best practices AI governance model evaluation and observability
- Lead end to end development of cloud native applications APIs and platform services
- Operate AI and data services with reliability and security best practices
- Provide hands on technical leadership through architecture reviews code reviews and mentoring
Perks/Benefits
- N/A
Skills/Tech-stack
AI Foundry | AI Observability | Agentic AI | App Service | Azure | Azure AI | Azure AI Foundry | Azure App | Azure App Service | Azure Data | Azure Data Factory | Azure Synapse | Azure Synapse Analytics | C# | Compliance | Continuous Delivery | Copilots | Data Factory | Generative AI | Java | Knowledge graphs | LLM orchestration | LLMOps | Language Model | Large Language Model | MLOps | Microsoft Fabric | Model Governance | Model Tuning | Observability | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | Scala | Security | Semantic Search | Synapse Analytics | Vector Database
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
Data Engineer | Engineer | Principal | Principal Data Engineer
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