Senior AI Systems Engineer
Raleigh, North Carolina, United States; Albuquerque, New Mexico, United States
R
USD 122K-188K (estimate) Senior-level Full Time
Tasks
- Apply infrastructure as code
- Assess system enhancements for scalability reliability cost efficiency
- Build MLops pipelines
- Collaborate across divisions on AI initiatives
- Conduct vulnerability management
- Deploy and manage model lifecycle
- Design AI infrastructure
- Develop and maintain architecture diagrams
- Ensure security and compliance
- Evaluate AI tools and frameworks
- Implement AI infrastructure monitoring
- Implement infrastructure automation
- Implement observability with logging and metrics
- Integrate AI tools and services
- Lead AI platform deployment
- Maintain AI documentation runbooks and procedures
- Maintain CI/CD pipelines
- Operationalize machine learning workflows
- Optimize AI infrastructure performance
- Package and test models
- Perform root cause analysis
- Perform secure architecture reviews
- Provide operational support
- Provide technical support and troubleshooting
- Set up alerting and incident response
- Support AI applications from development to production
- Use configuration management
Perks/Benefits
Skills/Tech-stack
Alerting | Bash | CI/CD | CMMC | Cause analysis | Configuration Management | Containers | GPU | Git | High Performance | High-Performance Computing | Hugging Face | Incident Response | Inference Optimization | Infrastructure as Code | Kubeflow | Kubernetes | LLM APIs | Langchain | Langgraph | Logging | MLOps | MLflow | Machine Learning | Metrics | Model Deployment | Model Serving | Monitoring | NIST | OAuth | Orchestration | Performance Computing | PyTorch | Python | Root Cause Analysis | Root cause | VLLM | “as-code”
Education
N/A
Roles
AI | AI Systems Engineer | Engineer | Senior AI Systems Engineer | Systems Engineer
Regions
Countries
States
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