AI Architect
Tasks
- Advise teams on model choice data readiness and infrastructure
- Architect RAG pipelines and agent driven applications
- Assess new technologies for efficiency and scalability
- Build scalable cloud architectures across Azure AWS or GCP
- Contribute to engineering standards security processes and governance
- Create model versioning deployment tracking and monitoring workflows
- Define scalable architecture patterns and standards
- Design end-to-end AI systems
- Design feature stores vector databases and data flows
- Establish retraining evaluation and responsible AI practices
- Integrate cloud based LLM services into enterprise solutions
- Lead architectural reviews for security performance and maintainability
- Produce architecture diagrams specifications and integration plans
- Provide guidance on prompt engineering and agent orchestration
- Recommend AI delivery tools frameworks and cloud services
- Translate business needs into technical designs and implementation plans
Perks/Benefits
Skills/Tech-stack
APIs | AWS | AWS Bedrock | Agent Orchestration | Azure | Azure AI | CI/CD | Data Pipelines | Deep learning | Distributed data | Docker | Feature Stores | Generative AI | Google Cloud | Kubernetes | Language Models | Large Language Models | MLOps | Machine Learning | Microservices | Model Governance | Model Monitoring | Prompt engineering | PyTorch | Python | RAG | Scikit-learn | TensorFlow | Vector Databases | Vertex AI
Education
Roles
AI | AI Architect | Architect | Learning Architect | Machine Learning Architect
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