AI Architect & Builder

Role Summary


Core Responsibilities

• Workflow Deconstruction Automation Strategy: Analyze business functions (sales, ops, supply chain, finance, CX)
• Workflow Deconstruction Automation Strategy: Break down workflows into decision trees and automation opportunities
• Workflow Deconstruction Automation Strategy: Identify high-ROI automation use cases
• Workflow Deconstruction Automation Strategy: Redesign processes for AI-first execution (not human-first)
• Agentic System Design: Design multi-step AI workflows (single agent + multi-agent systems)
• Agentic System Design: Inputs / outputs
• Agentic System Design: Memory structures
• Agentic System Design: Tool usage (APIs, DBs, SaaS tools)
• Agentic System Design: Decision logic
• Build systems that can: Think (LLMs)
• Build systems that can: Act (tools, APIs)
• Build systems that can: Learn (feedback loops)
• Build Implementation: Develop AI agents using OpenAI / Claude / LLM APIs
• Build Implementation: Agent frameworks (LangGraph, CrewAI, AutoGen, etc.)
• Build Implementation: Workflow tools (n8n, Zapier, Make, Retool)
• Build Implementation: Integrate with internal systems: ERP (SAP / Tally)
• Build Implementation: CRM
• Build Implementation: Shopify / marketplaces
• Build Implementation: Databases
• Build Implementation: Communication tools (WhatsApp, email, Slack)
• Build Implementation: Deploy production-ready systems (not prototypes)
• Automation Infrastructure: Build reusable internal automation frameworks
• Automation Infrastructure: Create orchestration layers across multiple agents
• Automation Infrastructure: Implement monitoring, logging, and failure handling
• Automation Infrastructure: Design fallback systems for edge cases
• Optimization Scaling: Continuously improve system accuracy, speed, and cost
• Optimization Scaling: Reduce human intervention over time
• Optimization Scaling: Scale automations across departments

Key Outcomes (What Success Looks Like)

• 50-80% reduction in manual operational work
• Fully automated workflows across key functions
• AI agents independently handling end-to-end tasks
• Minimal human oversight required for routine processes

Required Skills

Technical

• Strong experience with LLMs and prompt engineering
• Experience with agent frameworks (LangChain, LangGraph, CrewAI, etc.)
• API integrations and system design
• Familiarity with automation tools (n8n, Zapier, Make)
• Basic backend understanding (Python / JS preferred)

Systems Thinking

• Ability to convert messy real-world workflows into structured systems
• Strong understanding of business processes
• Optimization mindset (speed, cost, scalability)

Execution

• High ownership and bias for action
• Ability to ship fast and iterate
• Comfortable working with ambiguity
• Focus on outcomes, not just building tools

Good-to-Have

• Experience with RPA tools
• Exposure to ERP systems (SAP, Oracle, Tally)
• Experience in FMCG / manufacturing / D2C environments
• Understanding of data pipelines / analytics

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.