ROLE TITLE
We are looking for Virtual Professionals based in the Philippines, India, or United States.
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This is a fully remote position for the role of AI Systems Builder (Multi-Agent Orchestration & Backend Automation).
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Applications with an introduction video attached will be prioritized.
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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:
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multi-agent systems
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workflow automation engines
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backend infrastructure for AI agents
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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:
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unblock yourself without guidance
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design and implement full-stack AI workflows
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integrate APIs, databases, and agent orchestration layers
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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)
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Build and ship multi-agent orchestrator systems using Claude Code / agent frameworks
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Design agent roles, workflows, and memory structures for real business operations
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Implement coordination logic between agents (task delegation, state passing, retries)
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Ensure systems are production-ready (not demos or notebooks)
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Continuously refine agent behavior based on real-world execution outcomes
2. AI WORKFLOW AUTOMATION ENGINEERING
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Convert business workflows into automated AI-driven pipelines
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Build standalone agent SDKs and reusable automation modules
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Design systems that execute multi-step business processes without human intervention
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Ensure workflows are reliable, observable, and maintainable in production environments
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Optimize for failure recovery, not just successful execution paths
3. BACKEND + DATA SYSTEMS (POSTGRES / SUPABASE CORE)
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Design and implement PostgreSQL schemas for agent systems and workflows
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Build Supabase-backed applications powering AI agents and automations
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Ensure data integrity across multi-agent operations
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Structure databases for real-time agent execution and state tracking
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Debug and optimize backend performance when workflows break
4. API INTEGRATION & SYSTEM CONNECTIVITY
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Build and maintain production API integrations across business tools
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Connect AI agents to external systems (CRMs, property tools, communication tools)
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Handle authentication, rate limits, retries, and failure states
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Ensure integrations are stable and production-safe, not experimental scripts
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Debug end-to-end system flows when integrations fail
5. FULL SYSTEM SHIP & DEPLOYMENT OWNERSHIP
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Take systems from architecture build deployment production use
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Package AI systems into usable tools or SDK-like deliverables
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Ensure systems are deployable, maintainable, and configurable
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Write clean, production-grade code (not prototypes or notebooks)
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Maintain and improve systems after deployment based on real usage
6. SELF-DIRECTED ENGINEERING EXECUTION
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Identify missing requirements without being told
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Break down ambiguous system requests into buildable components
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Choose implementation paths independently
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Debug production issues without escalation dependency
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Maintain momentum without waiting for structured assignments
REQUIREMENTS (NON-NEGOTIABLE)
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Proven experience building and shipping multi-agent systems in production
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Knowledge or experience with OpenClaw, Hermes, or equivalent agent frameworks
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Strong backend engineering experience (PostgreSQL required)
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API integration experience in real production environments
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Strong proficiency in Python or TypeScript/JavaScript
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Comfortable working in CLI, Git, and deployment environments
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Ability to independently design and implement full systems end-to-end
If you have not shipped real AI systems (not demos), you are not qualified for this role.
BONUS EXPERIENCE (STRONGLY PREFERRED)
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Supabase production systems
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React (frontend for AI tools)
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GoHighLevel or HubSpot integrations
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Vector databases (Pinecone, Weaviate, etc.)
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Docker-based deployments
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Real estate operations system experience
WHAT WE ACTUALLY CARE ABOUT
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You have shipped working AI systems used in real workflows
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You understand how to build agent systems that don’t break in production
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You can design systems, not just code features
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You unblock yourself without waiting for instructions
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You build infrastructure that other people rely on
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You think in systems, not prompts or scripts
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You deliver working tools, not prototypes
WHAT THIS ROLE IS NOT
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Not a prompt engineering role
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Not a chatbot-building or UI-only AI role
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Not a research or experimentation position
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Not a no-code automation or Zapier-style builder role
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Not a junior Python scripting job
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Not a tutorial-following “AI enthusiast” role
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Not a role where someone defines every architecture decision for you
POSITION DETAILS
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Full-time contractor
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100% remote (global)
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Flexible hours (performance-driven, not time-driven)
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Fast-paced engineering environment
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Small team, high ownership, high autonomy
APPLICATION INSTRUCTIONS
Include:
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Resume
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Links to shipped systems (required)
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GitHub repos
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live tools
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agent systems
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deployed workflows
Working systems matter more than resumes.
We will ignore applications without real shipped work.
