AI Architect
Charlotte, North Carolina, USA
USD 125K-166K (estimate) Senior-level Full Time
Tasks
- Apply responsible AI practices
- Architect production AI and ML solutions
- Create reference architectures for AI workflows
- Define MLOps standards
- Define enterprise AI architecture
- Design RAG systems
- Design REST APIs for AI services
- Design embedding pipelines
- Design inference services
- Design intelligent agents at scale
- Ensure observability and cost monitoring
- Establish standards for LLM applications
- Evaluate AI models for enterprise use
- Implement model lifecycle management
- Implement monitoring and retraining
- Implement serverless microservices patterns
- Integrate AI services with core applications
- Lead architecture design reviews
- Lead proof of concept initiatives
- Lead solution designs for vector databases
- Mentor AI and software engineering teams
Perks/Benefits
- 401k with company match
- Career growth
- Employee discounts
- Financial wellness planning
- Health, dental and vision coverage
- High visibility leadership partnership
- Tuition reimbursement
Skills/Tech-stack
AI Search | Azure | Azure AI | Azure AI Search | Azure DevOps | Azure Machine Learning | Azure OpenAI | CI/CD | Csharp | Data Governance | Data Lineage | Data Modeling | Docker | Embeddings | Event Driven | Event-driven architecture | Feature Stores | Git | Hallucination mitigation | Kubernetes | Lakehouse | Langchain | MLOps | MLflow | Machine Learning | Microservices | Microsoft Fabric | Model registries | Model versioning | Node.js | Privacy Compliance | Python | RAG | REST APIs | Responsible AI | Retrieval-Augmented Generation | Security | Semantic Kernel | Serverless | Vector Databases | Vector indexing
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Architect | Architect | Learning Architect | Machine Learning Architect
Regions
Countries
States
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