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About the role
Architect multi-agent systems: Design patterns for orchestration, memory management, and tool integration using frameworks like LangChain or CrewAI. Develop and deploy GenAI agents for tasks such as:
Requirement validation and auto-correction Test strategy and scenario generation Automation script generation and self-healing Data synthesis and performance planning
Integrate with enterprise platforms: Ensure compatibility with workflow tools, CI/CD pipelines, and observability dashboards. Implement security and governance: Role-based access control, audit logging, and responsible AI guardrails. Optimize performance and cost: Reduce token usage, latency, and operational overhead through prompt engineering and caching strategies. Mentor teams on GenAI architecture, prompt design, and best practices. Hands-on experience with LangChain/CrewAI, Python/TypeScript, and API integrations. Strong knowledge of cloud-native architecture (Docker, Kubernetes, AWS/GCP/Azure). Familiarity with RBAC, security frameworks, and compliance standards. Knowledge of vector databases (PGVector, Pinecone) and hybrid RAG strategies. 15+ years of experience
ai agent,autogen,kubernetes,cloud computing,
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