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About
with
Agentic AI experience
Core must-haves (screen for these explicitly)
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 they're 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.
Proficiency in google bigquery for data warehousing and analytics.
Strong sql skills for querying and managing large datasets.
Advanced knowledge of python programming language for data manipulation and analysis.
Experience with google dataflow for real-time data processing and etl pipelines.
Strong problem-solving and analytical skills.
Excellent communication and leadership abilities to effectively lead a technical team.
Languages
- English
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