DevOps Engineer with
Agentic AI experienceCore 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.