Agentic AI Architect

Inabia Solutions and Consulting, Inc.

$120K — $150K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Proven track record of deploying AI assistants and chatbots in production.
  • Deep expertise in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
  • Experience designing cloud-native architectures for enterprise-scale AI.
  • Proficiency with Vertex AI, Dialogflow, and modern AI frameworks.
  • Strong background in multi-agent system design and task execution.
  • Experience in establishing AI governance and engineering standards.
  • Capability to integrate AI with enterprise systems across various domains.

Responsibilities

  • Design and implement enterprise-grade Generative AI architectures for chatbots and automation.
  • Architect and deploy production-ready AI agents capable of reasoning and planning.
  • Create scalable AI platforms for model and tool reuse across business units.
  • Define architectural standards and best practices for AI adoption.
  • Develop LLM-powered chatbots using Vertex AI and Dialogflow.
  • Build conversational experiences for customer support and operational workflows.
  • Implement advanced prompt engineering strategies to enhance user experience.

Benefits

  • Work on innovative AI projects in a leading technology environment.
  • Collaborate with a skilled team of AI and technology professionals.
  • Opportunity for professional growth in a dynamic field.
  • Access to the latest AI technologies and resources.
  • Flexible work arrangements to promote work-life balance.
Full Job Description
Agentic AI Architect
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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