Scale Virtually
Real Estate
AISystemsBuilder(Multi-AgentOrchestration&BackendAutomation)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“AI Systems Builder (Multi-Agent Orchestration & Backend Automation) at Scale Virtually. Skills: Multi-agent systems, Workflow automation, Backend systems. Build and ship multi-agent orchestrator systems. Design agent roles, workflows, and memory structures”
What You'll Achieve.
Ship working systems; Build infrastructure for others
Industry & Context.
Unblock yourself; Troubleshooting
What They're Looking For.
Must Have
Proven experience building and shipping multi-agent systems in production, Hands-on experience with OpenClaw, Hermes, or equivalent agent frameworks, Backend engineering experience, API integration experience in real production environments, Proficiency in Python or TypeScript/JavaScript, Comfortable working in CLI, Git, and deployment environments, Ability to independently design and implement full systems end-to-end
Nice to Have
Supabase production systems, React frontend for AI tools, GoHighLevel or HubSpot integrations, Vector databases experience, Docker-based deployments, Real estate operations system experience
What You'll Do.
Build and ship multi-agent orchestrator systems
and memory structures
Implement coordination logic between agents
Ensure systems are production-ready
Refine agent behavior based on outcomes
Convert business workflows into automated AI-driven pipelines
Build standalone agent SDKs
Design systems that execute multi-step business processes
Ensure workflows are reliable and maintainable
Optimize for failure recovery
Design and implement PostgreSQL schemas
Build Supabase-backed applications
Ensure data integrity across operations
Structure databases for agent execution
Debug and optimize backend performance
Build and maintain production API integrations
Connect AI agents to external systems
Handle authentication
Ensure integrations are stable and production-safe
Debug end-to-end system flows
Take systems from architecture to production use
Package AI systems into usable tools
Ensure systems are deployable
Write production-grade code
Maintain and improve systems after deployment
Identify missing requirements
Break down ambiguous system requests
Choose implementation paths independently
Debug production issues without escalation
Maintain momentum without structured assignments
How You'll Work.
Team & Collaboration
Small, fast-moving team
Communication Scope
Video calls
Process & Methodology
Agile
Full Job Description
### ROLE TITLE We are looking for Virtual Professionals based in the Philippines, India, or United States. * This is a fully remote position for the role of AI Systems Builder (Multi-Agent Orchestration & Backend Automation). * Applications with an introduction video attached will be prioritized. * Due to the fully remote nature of this role, it is important that candidates are comfortable communicating on video calls. ### ROLE SUMMARY You build and ship production-grade AI systems that run real business workflows end-to-end. This is not an experimentation or research role. You are building: * multi-agent systems * workflow automation engines * backend infrastructure for AI agents * deployed systems used by real estate operators and businesses You will work inside a small, fast-moving team shipping real systems for real clients—not prototypes, not demos. You are expected to: * unblock yourself without guidance * design and implement full-stack AI workflows * integrate APIs, databases, and agent orchestration layers * ship working systems, not isolated components If you need step-by-step instructions, rely on tutorials, or struggle turning architecture into deployed systems, you will fail in this role. Filtering signal: This role is not for candidates who have only used AI tools, but never shipped multi-agent systems in production. ### CORE RESPONSIBILITIES (REAL EXECUTION BEHAVIOR) ### 1\. MULTI-AGENT SYSTEM DEVELOPMENT (CORE ENGINEERING FUNCTION) * Build and ship multi-agent orchestrator systems using Claude Code / agent frameworks * Design agent roles, workflows, and memory structures for real business operations * Implement coordination logic between agents (task delegation, state passing, retries) * Ensure systems are production-ready (not demos or notebooks) * Continuously refine agent behavior based on real-world execution outcomes ### 2\. AI WORKFLOW AUTOMATION ENGINEERING * Convert business workflows into automated AI-driven pipelines * Build standalone agen
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