AI Architect

Tasks

• Apply MLOps and LLMOps best practices
• Build LLM and RAG pipelines
• Contribute to security compliance for AI systems
• Create reusable reference architectures
• Design production AI solutions
• Develop agentic workflows
• Establish monitoring and observability
• Implement vector search with embeddings
• Support model governance and lifecycle management
• Support sales pre sales RFP responses proposals
• Translate customer needs into AI architectures

Perks/Benefits

• Flexible working model
• Hybrid work model
• Open culture
• Professional growth
• Work-life balance

Skills/Tech-stack

AI Foundry | AWS SageMaker | Agentic Workflows | Azure AI | Azure AI Foundry | CI/CD | Embeddings | GDPR | Google Vertex | Google Vertex AI | LLMOps | Langchain | Langgraph | Language Models | Large Language Models | MLOps | Machine Learning | Model Governance | Monitoring | Observability | Prompt engineering | Python | Retrieval-Augmented Generation | Vector Databases | Vector Search | Vertex AI