AI Automation Engineer
Workflow automation across CRM, email, calendars, reporting, lead response, and business APIs.
Explore AI automation →About Mark Carmona
AI automation and agent engineering grounded in real operations.
Mark Carmona is a remote AI automation and AI agent engineer in the Philippines. He builds systems that receive work, reason through it, call tools, update records, and return a verified result.
1,346ClawBridge Codex commits at the July 2026 site update
36Repository tags documenting an actively versioned project
86%TypeScript codebase for the public agent platform
12+Supported communication and work channels
From repetitive operations to production AI systems
Mark’s perspective comes from working around repetitive follow-ups, data entry, scheduling, customer questions, reporting, and disconnected business tools. That experience shapes his engineering approach: begin with the operating bottleneck, then decide where reasoning, automation, memory, or human approval belongs.
His work spans ClawBridge, ClawBridge Codex, OpenClaw and Hermes-Agent, OpenAI Codex, TypeScript, Node.js, Docker, Hindsight memory, MCP integrations, CRM systems, outreach workflows, and production websites.
What Mark means by an AI agent
An agent is not merely a chat interface. A production agent should have a bounded job, explicit tools, controlled access, observable execution, and a known path for retries or human escalation. The surrounding system matters as much as the model.
Positioning: AI Automation & AI Agent Engineer · Philippines · Available for remote builds worldwide.
Public evidence
ClawBridge Codex is the principal public example. It uses a Node host to orchestrate per-session agent containers, keeps credentials host-side, supports multiple communication channels, and integrates persistent memory. The source repository and project limitations are linked from the case study.
Engineering services
Choose the system, not just the keyword.
Each service page describes a distinct delivery scope with public project evidence, technical boundaries, and a clear handoff path.
AI Agent Engineer
Tool-using agents with memory, approvals, multi-step execution, and failure handling.
Explore AI agent development →Self-Hosted AI Agent Developer
Client-owned runtimes with Docker isolation, host-side secrets, storage, and monitoring.
Explore self-hosted AI →OpenClaw Developer
OpenClaw and Hermes-Agent deployment, hardening, skills, integrations, and migration.
Explore OpenClaw development →Remote AI Engineer
Project-based AI agent and automation delivery for distributed teams worldwide.
Explore remote delivery →ClawBridge Codex
Review the architecture and public repository behind Mark’s self-hosted agent work.
Review the case study →Available for remote builds
Bring me the workflow that keeps falling back to manual work.
I’ll help identify whether it needs an AI agent, deterministic automation, an OpenClaw deployment, a custom integration, or a simpler system.
Email Mark Carmona →