We are looking for a highly experienced AI Agent Developer who has already built and deployed production-grade AI systems using Claude, OpenAI, MCP servers, and agentic workflows.
This is not a role for someone experimenting with AI or learning on the job. We need someone who deeply understands how Claude and GPT models behave in real-world environments, including context management, tool calling, memory strategies, agent orchestration, failure modes, and production reliability.
- Design, build, and deploy production-grade AI agents using Claude, OpenAI, MCP, and agentic workflow frameworks.
- Develop Claude Agents, Claude Code workflows, Claude Skills, Custom GPTs, and OpenAI Assistants.
- Build and maintain MCP servers, connectors, and shared tooling that work across multiple AI platforms.
- Integrate AI systems with platforms such as ServiceM8, Xero, Microsoft 365, HubSpot, GoHighLevel, Wunderbuild, and other client applications.
- Create REST API wrappers, authentication layers, OAuth integrations, webhooks, and middleware services.
- Architect scalable multi-agent systems, memory frameworks, and context management strategies.
- Troubleshoot AI agent failures, identify root causes, and implement reliable production solutions.
- Deliver solutions from scope documents with minimal supervision while collaborating with clients during Australian business hours.
- Ensure security, scalability, maintainability, and production readiness of all AI implementations.
- Proven experience building and deploying MCP servers used by real customers in production environments.
- Hands-on experience with Anthropic Claude and OpenAI APIs, including tool use, function calling, agent orchestration, and workflow automation.
- Deep understanding of context management, memory architectures, prompt engineering, agent failure modes, and AI system reliability.
- Strong experience with third-party API integrations, OAuth, webhooks, authentication flows, and REST-based architectures.
- Advanced proficiency in Node.js and/or Python, including serverless and cloud-based deployments.
- Ability to independently design, build, test, and deploy solutions from technical specifications.
- Experience with n8n, Make, Zapier, or similar automation platforms.
- Experience with AWS, Azure, or Google Cloud deployments.
- Knowledge of RAG architectures, vector databases, and AI knowledge systems.
