AI Engineer
Tasks
- Apply MLOps and LLMOps best practices
- Build AI agents and agentic workflows
- Build MCP servers and tools
- Build and operate vector databases
- Collaborate with data and platform teams
- Create AI-powered data pipelines
- Create monitoring and evaluation frameworks
- Design production AI solutions
- Develop prompt frameworks
- Implement RAG solutions
- Implement Responsible-AI guardrails
- Integrate AI agents with enterprise systems
- Integrate LLM APIs
- Manage version control and CI/CD pipelines
- Perform model lifecycle management
- Produce technical documentation and architecture designs
Perks/Benefits
- N/A
Skills/Tech-stack
AI Observability | Access Control | Anthropic Claude | Azure AI | Azure OpenAI | CI/CD | Cloud Deployments | Containerization | Docker | LLMOps | Langchain | Langgraph | Language Models | Large Language Models | Lifecycle Management | Llamaindex | MLOps | Model Context Protocol | Model Evaluation | Model Lifecycle | Model Lifecycle Management | OpenAI | Performance Monitoring | Privacy | Python | RAG | Responsible AI | Retrieval-Augmented Generation | Security | Testing | Vector Databases
Education
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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