About The Position

We are seeking a highly experienced AI Automation Architect to lead the design and implementation of next-generation intelligent automation platforms. This role combines AI Agents, Agentic Workflows, Enterprise Automation, and Cloud-Native Architecture to deliver scalable business solutions. The ideal candidate should possess strong software engineering and architecture expertise, hands-on experience with modern AI frameworks and automation platforms, and a proven track record of building enterprise-grade automation ecosystems.

Requirements

  • Bachelors or Masters degree in Computer Science, Engineering, Information Technology, or a related field.
  • 10+ years of experience in Software Engineering, Automation, Solution Architecture, or AI Engineering.
  • 3+ years of hands-on experience building AI-powered automation solutions, AI Agents, or Agentic Platforms.
  • Proven experience delivering enterprise-scale automation and AI transformation initiatives.
  • Must have experience on AI Dev Tools (Copilot, Claude Code / Codex).

Nice To Haves

  • Experience with RPA platforms such as UiPath, Automation Anywhere, or Power Automate.
  • Experience modernizing traditional RPA implementations using AI Agents and Agentic Automation approaches.
  • Exposure to process mining, intelligent document processing (IDP) with Vision Models, and enterprise integration patterns.

Responsibilities

  • Architect and implement AI-powered automation solutions using Large Language Models (LLMs), AI Agents, and Agentic Workflows.
  • Design autonomous and human-in-the-loop agent systems for planning, reasoning, and task execution.
  • Build multi-agent architectures integrating enterprise applications, APIs, databases, SaaS platforms, and business processes.
  • Implement Retrieval-Augmented Generation (RAG), Browser Agents, and MCP-based or Skill based integrations.
  • Design scalable workflow orchestration solutions using platforms such as n8n, Zapier, and custom automation frameworks.
  • Integrate AI agents into operational and business workflows with reusable automation patterns and best practices.
  • Design scalable cloud-native and event-driven architectures for AI automation platforms.
  • Establish standards for security, reliability, maintainability, and operational excellence.
  • Collaborate across engineering and business teams to deliver enterprise-grade solutions.
  • Implement end-to-end monitoring, tracing, logging, and auditability for AI agents and automation workflows.
  • Drive performance optimization, cost management, incident analysis, and operational governance.
  • Ensure compliance, security, and responsible AI practices.
  • Build feedback loops and evaluation frameworks to improve agent performance and accuracy.
  • Optimize prompts, workflows, and decision-making using telemetry, analytics, and user feedback.
  • Drive continuous platform enhancement through measurement, experimentation, and automation.

Benefits

  • Remote Work
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