Senior Architect for AI Automation Platform
Budget / SalaryHourly project
TypeFreelance project
LocationRemote
Posted1 hour ago
We are looking for an experienced Senior AI Systems & Backend Architect to design, build, and deploy an end-to-end, production-ready AI automation platform.
The system will combine real-time voice handling, autonomous reasoning agents with standardized tool integrations, asynchronous task processing, and a modern web dashboard.
Scope of Work & Deliverables:
AI Agents & Model Integration:
Implement agentic reasoning workflows using Anthropic Claude and advanced prompt engineering.
Architect Model Context Protocol (MCP) servers and tool definitions for structured, reliable database and third-party data querying.
Integrate conversational voice bots using Vapi and Twilio over real-time streaming WebSockets.
Backend Architecture & Distributed Processing:
Build high-concurrency, asynchronous API microservices using Python (FastAPI), Golang, or Node.js.
Set up distributed task queues and message handling (Redis) to decouple heavy LLM calls from synchronous user requests.
Design relational/embedded database schemas (SQLite / transactional stores) with secure OAuth2 authentication flows.
Workflow Automation & Integrations:
Build robust event-driven webhook connectors and automated multi-step workflows using self-hosted n8n and Zapier.
Ensure comprehensive API error handling, rate-limit management, and deterministic fallback routines.
Frontend & MVP Interface:
Build a clean, responsive frontend dashboard using React.js for user management, agent monitoring, and workflow visualization.
Cloud Infrastructure & DevOps:
Containerize all services using multi-stage Docker builds.
Provision and manage cloud resources on Microsoft Azure using Terraform (Infrastructure as Code).
Deliver clear architecture diagrams, API schema documentation, and deployment guides.
Required Technical Skills & Qualifications:
Strong hands-on experience in Python (FastAPI), Node.js, or Golang.
Proven background in AI Model Integration (Claude API, MCP, Function Calling, Prompt Engineering).
Practical experience with Voice AI (Vapi / Twilio) and real-time streaming protocols.
Experience with Docker, Terraform, and Microsoft Azure.
Familiarity with frontend integration using React.js.
Strong foundation in distributed systems, asynchronous design, and software architecture.
To Apply:
Please submit a brief breakdown of:
Your direct architectural approach for low-latency LLM/voice execution.
Similar AI pipelines or backend architectures you have built.
Your estimated timeline and milestone structure for delivering an initial MVP.
Project Tags:
Python • FastAPI • Artificial Intelligence • AI Automation • Model Context Protocol (MCP) • Docker • Microsoft Azure • React.js • Golang • Node.js • n8n • Vapi • Twilio • Terraform • Distributed Systems • Software Architecture
The system will combine real-time voice handling, autonomous reasoning agents with standardized tool integrations, asynchronous task processing, and a modern web dashboard.
Scope of Work & Deliverables:
AI Agents & Model Integration:
Implement agentic reasoning workflows using Anthropic Claude and advanced prompt engineering.
Architect Model Context Protocol (MCP) servers and tool definitions for structured, reliable database and third-party data querying.
Integrate conversational voice bots using Vapi and Twilio over real-time streaming WebSockets.
Backend Architecture & Distributed Processing:
Build high-concurrency, asynchronous API microservices using Python (FastAPI), Golang, or Node.js.
Set up distributed task queues and message handling (Redis) to decouple heavy LLM calls from synchronous user requests.
Design relational/embedded database schemas (SQLite / transactional stores) with secure OAuth2 authentication flows.
Workflow Automation & Integrations:
Build robust event-driven webhook connectors and automated multi-step workflows using self-hosted n8n and Zapier.
Ensure comprehensive API error handling, rate-limit management, and deterministic fallback routines.
Frontend & MVP Interface:
Build a clean, responsive frontend dashboard using React.js for user management, agent monitoring, and workflow visualization.
Cloud Infrastructure & DevOps:
Containerize all services using multi-stage Docker builds.
Provision and manage cloud resources on Microsoft Azure using Terraform (Infrastructure as Code).
Deliver clear architecture diagrams, API schema documentation, and deployment guides.
Required Technical Skills & Qualifications:
Strong hands-on experience in Python (FastAPI), Node.js, or Golang.
Proven background in AI Model Integration (Claude API, MCP, Function Calling, Prompt Engineering).
Practical experience with Voice AI (Vapi / Twilio) and real-time streaming protocols.
Experience with Docker, Terraform, and Microsoft Azure.
Familiarity with frontend integration using React.js.
Strong foundation in distributed systems, asynchronous design, and software architecture.
To Apply:
Please submit a brief breakdown of:
Your direct architectural approach for low-latency LLM/voice execution.
Similar AI pipelines or backend architectures you have built.
Your estimated timeline and milestone structure for delivering an initial MVP.
Project Tags:
Python • FastAPI • Artificial Intelligence • AI Automation • Model Context Protocol (MCP) • Docker • Microsoft Azure • React.js • Golang • Node.js • n8n • Vapi • Twilio • Terraform • Distributed Systems • Software Architecture
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