Senior AI Integration Engineer Build Enterprise AI Automation & Workflow Platform

We are looking for an experienced **Senior Agentic AI Engineer** to design and build a production-ready multi-agent AI platform that automates customer support, internal operations, and business workflows. This is **not** a chatbot or simple prompt engineering project. We are building an intelligent network of AI agents that collaborate, share context, make decisions, use external tools, and execute complex workflows with minimal human intervention. The platform should be modular, scalable, and capable of supporting multiple business teams while maintaining security, observability, and human approval for critical actions. Project Objective Develop a complete Agentic AI platform capable of automating business operations from customer inquiry through task execution and reporting. The platform should leverage modern AI technologies including: * OpenAI GPT * Claude * Gemini * MCP (Model Context Protocol) * LangGraph * CrewAI * AutoGen * OpenAI Agents SDK * Retrieval-Augmented Generation (RAG) * Vector Databases * Workflow Automation AI Agent Ecosystem Customer Support Agent * Answer customer questions * Retrieve company knowledge * Resolve common issues * Escalate complex cases Sales Agent * Qualify incoming leads * Schedule meetings * Generate proposals * Update CRM Knowledge Management Agent * Crawl websites * Index internal documentation * Process PDFs and documents * Continuously update the knowledge base Research Agent * Competitor research * Industry monitoring * Market intelligence * Opportunity discovery Workflow Orchestrator * Coordinate all AI agents * Assign tasks * Manage dependencies * Track workflow completion Document Processing Agent * Extract structured data * OCR processing * Classification * Validation Data Analytics Agent * Build reports * Analyze KPIs * Detect anomalies * Generate business insights QA & Compliance Agent * Verify AI responses * Ensure policy compliance * Fact checking * Audit outputs DevOps Agent * Monitor deployments * Analyze logs * Detect incidents * Recommend fixes Executive Assistant Agent * Summarize meetings * Generate action items * Draft emails * Schedule follow-ups Expected Workflow Customer Request → Knowledge Retrieval → Task Planning → Multi-Agent Collaboration → Tool Execution → Human Approval (if required) → Completion → Learning & Knowledge Update Each completed workflow should improve future performance through evaluation, feedback, and knowledge refinement. Technical Requirements The platform should include: * Multi-agent orchestration * MCP-compatible architecture * Long-term memory management * RAG with vector databases * Tool and function calling * REST APIs * Webhooks * Authentication and authorization * Human-in-the-loop approval workflows * Background task processing * Event-driven architecture * Monitoring and logging * Retry mechanisms and fault recovery * Modular and scalable design * Comprehensive documentation Preferred Technology Stack * Python * FastAPI * LangGraph * CrewAI * AutoGen * OpenAI Agents SDK * OpenAI API * Anthropic Claude API * Gemini API * PostgreSQL * Redis * Pinecone, Weaviate, pgvector, or Qdrant * Docker * Kubernetes * AWS, Azure, or Google Cloud * n8n * Kafka or RabbitMQ * Prometheus * Grafana Deliverables The selected engineer will deliver: * Complete multi-agent architecture * Agent communication framework * Memory architecture * Knowledge management system * Tool integration layer * API services * Workflow orchestration engine * Deployment documentation * Testing framework * Monitoring and observability setup * Production-ready implementation Required Experience Applicants should have experience with: * Building production Agentic AI systems * LLM application development * Multi-agent orchestration * Retrieval-Augmented Generation (RAG) * AI workflow automation * Vector databases * Cloud infrastructure * Python backend development * Distributed systems * Production AI deployments Experience with enterprise AI platforms, autonomous workflows, and large-scale AI systems is highly preferred. Engagement Details * Contract Type: Long-term * Location: Worldwide * Experience Level: Senior / Expert * Hours: 30–40 hours per week * Project Type: Hourly or Fixed Price (depending on experience) How to Apply Please include the following in your proposal: * A brief overview of your experience building Agentic AI platforms * Examples of production multi-agent systems you have developed * Your preferred orchestration framework and why * Experience with LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, or similar technologies * Cloud platforms you have worked with * GitHub, portfolio, or project links * Your availability and hourly rate