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Über
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.
Strong proficiency in devops practices and tools.
Proficient in python programming language.
Experience with kubernetes and containerization technologies.
Knowledge of ci/cd pipelines and automation tools.
Ability to lead and motivate a technical team effectively.
Excellent problem-solving and communication skills.
Strong analytical and decision-making abilities.
Certifications:
Relevant certifications in DevOps, python, or
Kubernetes
are a plus.
Sprachkenntnisse
- English
Hinweis für Nutzer
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