- Applied Agentic AI engineering experience: evidence of building Agentic workflows - ideally delivered into a real project.
- Modern multi-agent architecture experience: hands-on designing/implementing systems where multiple AI Agents collaborate.
- Strong understanding of agentic frameworks/tools: candidates must be able to name the frameworks used explain why chosen and describe components.
- Protocols knowledge with practical relevance: working knowledge (preferably applied) of MCP A2A ACP-and ability to explain how theyre used in real-world AI Agent systems.
- Architecture & design contribution capability: candidate should be able to contribute to solution architecture discuss trade-offs/pros-cons and guide design decisions for agentic systems.
- Design and develop scalable data engineering solutions on Google Cloud Platform using Golang
- Build and maintain high-performance data pipelines and processing systems
- Work closely with architects and cross-functional teams to implement cloud-native data solutions
- Ensure data quality reliability and performance across data platforms
- Contribute to best practices standards and optimization of data workflows
Applied Agentic AI engineering experience: evidence of building Agentic workflows - ideally delivered into a real project. Modern multi-agent architecture experience: hands-on designing/implementing systems where multiple AI Agents collaborate. Strong understanding of agentic frameworks/tools: ca...
- Applied Agentic AI engineering experience: evidence of building Agentic workflows - ideally delivered into a real project.
- Modern multi-agent architecture experience: hands-on designing/implementing systems where multiple AI Agents collaborate.
- Strong understanding of agentic frameworks/tools: candidates must be able to name the frameworks used explain why chosen and describe components.
- Protocols knowledge with practical relevance: working knowledge (preferably applied) of MCP A2A ACP-and ability to explain how theyre used in real-world AI Agent systems.
- Architecture & design contribution capability: candidate should be able to contribute to solution architecture discuss trade-offs/pros-cons and guide design decisions for agentic systems.
- Design and develop scalable data engineering solutions on Google Cloud Platform using Golang
- Build and maintain high-performance data pipelines and processing systems
- Work closely with architects and cross-functional teams to implement cloud-native data solutions
- Ensure data quality reliability and performance across data platforms
- Contribute to best practices standards and optimization of data workflows
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