Principal AI Engineer
Tasks
- Build production backend services
- Contribute through development and code reviews
- Define platform patterns and implementation standards
- Design cloud native foundations
- Design scalable architectures for AI applications
- Drive architectural decisions across service boundaries
- Establish observability and reliability standards
- Evaluate emerging AI cloud and platform technologies
- Lead architecture security and governance reviews
- Produce architecture and design documentation
- Translate requirements into secure scalable solutions
Perks/Benefits
- N/A
Skills/Tech-stack
AI Observability | API Design | AWS | Access Management | Agent Orchestration | Azure | CI/CD | Cloud Native | Cloud platform | CloudFormation | Containers | Continuous Delivery | Disaster Recovery | Distributed Systems | Evaluation Frameworks | Event Driven | Event-driven architecture | Google Cloud | Google Cloud Platform | Helm | Identity and Access Management | Identity and access | Incident Management | Infrastructure as Code | Kubernetes | Lifecycle Management | Microservices | Model Lifecycle | Model Lifecycle Management | Monitoring | Network Security | Observability | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | SLO | Terraform | “as-code”
Education
N/A
Roles
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