Lead design, development, and deployment of enterprise-scale Generative and Agentic AI solutions. Architect production-ready multi-agent systems, LLM-powered chatbots, and scalable AI platforms. Define standards, governance, guardrails, and best practices; integrate AI with enterprise systems and implement prompt engineering and RAG strategies to improve conversational and automation workflows.
Inabia is seeking an Agentic AI Architect to lead the design, development, and deployment of enterprise-scale Generative AI and Agentic AI solutions. This role requires deep expertise in designing enterprise AI ecosystems, enabling intelligent multi-agent workflows, and integrating AI solutions with enterprise systems at scale. The ideal candidate will establish governance, guardrails, and engineering standards to ensure scalable, secure, and reliable AI adoption across multiple business domains.
Responsibilities
- Design and implement enterprise-grade Generative AI and Agentic AI architectures supporting chatbot, assistant, and intelligent automation platforms.
- Architect and deploy production-ready AI agents and multi-agent systems capable of reasoning, planning, tool invocation, workflow orchestration, and autonomous task execution.
- Design scalable AI platforms enabling reuse of models, prompts, tools, and shared services across multiple business units and use cases.
- Define architecture standards, design patterns, and best practices for enterprise AI adoption.
- Design and develop LLM-powered chatbots and AI assistants using technologies such as Vertex AI, Dialogflow, and modern AI frameworks.
- Build conversational experiences for customer support, knowledge management, employee productivity, and operational workflows.
- Implement advanced prompt engineering strategies, prompt libraries, and optimization techniques to improve response quality and user experience.
Key Qualifications
- Proven track record of delivering AI assistants, chatbots, and autonomous agent platforms into production environments.
- Deep expertise in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
- Experience designing cloud-native architectures and enterprise-scale AI ecosystems.
- Proficiency with Vertex AI, Dialogflow, and modern AI and ML frameworks.
- Strong background in multi-agent system design, workflow orchestration, and autonomous task execution.
- Experience establishing AI governance frameworks, guardrails, and engineering standards.
- Demonstrated ability to integrate AI solutions with enterprise systems across diverse business domains.
Preferred Qualifications
- Hands-on experience with advanced prompt engineering strategies and structured prompt library management.
- Background delivering conversational AI solutions for customer support, knowledge management, or employee productivity use cases.
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