AI Engineer
Tasks
- Build and operate Azure AI platform components
- Collaborate with cross functional teams to deliver production AI services
- Create observability dashboards and alerts
- Define and apply architecture guardrails for security and networking
- Develop MLOps and LLMOps CI CD pipelines
- Implement GenAI capabilities with RAG patterns and vector databases
- Improve developer productivity with reusable templates and automation
- Own reusable deployment patterns and evaluation harnesses
- Package and deploy AI services with Docker and Kubernetes
Perks/Benefits
Skills/Tech-stack
API Design | Authentication | Authorization | Azure DevOps | Azure Machine Learning | CI/CD | Cost monitoring | Databricks | Docker | Drift Detection | Embeddings | GitHub | Hallucination detection | Kubernetes | Latency monitoring | ML model registry | MLflow | Machine Learning | Model Drift | Model Drift Detection | Model Evaluation | Model Monitoring | Model Registry | Network Security | Prompt engineering | Python | Retrieval-Augmented Generation | Token Monitoring | Vector Database
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer
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