AI Systems Engineer (LLM & AI Agent Development)

About the Role

We are looking for a highly technical AI Systems Engineer to help build, maintain, and expand a growing ecosystem of AI-powered applications, autonomous agents, and internal software systems.

This is an execution-focused engineering role. You will work directly with the founder to implement AI architectures, build new AI-driven features, improve existing systems, and rapidly deliver production-ready solutions.

We are specifically looking for someone who has built sophisticated AI systems in production—not someone who has simply used ChatGPT or experimented with prompt engineering.

Responsibilities

AI Systems Development

• Build and maintain AI-powered web applications.
• Develop and improve autonomous AI agent systems.
• Implement multi-agent workflows and orchestration.
• Build AI systems where multiple agents coordinate under a master orchestrator.
• Develop recursive AI workflows and advanced automation pipelines.
• Integrate LLMs into production applications and internal tools.

Product & Platform Development

• Expand and maintain an internally developed CRM platform.
• Build new features across multiple AI-powered products.
• Improve production systems through debugging, optimization, and ongoing enhancements.
• Build scalable backend services and APIs.
• Collaborate directly with the founder to rapidly execute product ideas.

Integrations & Automation

• Integrate AI applications with HubSpot and other business systems.
• Build API integrations between internal platforms and third-party applications.
• Improve workflow automation and data synchronization across multiple systems.
• Support AI-powered business assistants and internal automation tools.

AI Architecture & Agent Ecosystems

• Build and maintain graph memory architectures.
• Design secure information-sharing between AI agents.
• Implement memory management and data segmentation strategies.
• Ensure privacy controls and security boundaries across AI systems.
• Optimize AI performance, reliability, and scalability.

Required Experience & Skills

Must-Have

• 5+ years of professional software engineering experience.
• Strong experience building production AI applications.
• Proven experience developing autonomous AI agent systems.
• Experience implementing multi-agent orchestration and AI workflows.
• Strong Python development experience.
• Strong Node.js development experience.
• Working knowledge of Java.
• Experience integrating Large Language Models (LLMs) into production software.
• Strong prompt engineering experience for production environments.
• Experience building AI systems with graph memory and agent memory management.
• Experience designing secure AI architectures with data segmentation and privacy controls.
• Experience integrating APIs and business platforms.
• Hands-on experience integrating HubSpot or Salesforce into custom applications.
• Strong understanding of modern web application development.
• Experience using:
• Claude Code
• Cursor
• Replit
• OpenClaw (or equivalent AI engineering frameworks)
• Excellent written and spoken English communication skills.
• Ability to work independently with minimal supervision.

What Makes You a Strong Fit

• You have built sophisticated AI systems that are running in production.
• You enjoy implementing complex technical solutions quickly and accurately.
• You are comfortable working directly with a founder and turning ideas into working software.
• You proactively solve problems without waiting for detailed specifications.
• You thrive in fast-moving startup environments.
• You communicate clearly and are comfortable discussing technical topics live with stakeholders.

What Does a Typical Day Look Like?

You'll spend most of your day building and improving AI-powered applications, expanding autonomous agent workflows, integrating business systems, and implementing new features across multiple products.

You'll work closely with the founder to execute technical requirements, optimize production systems, build new AI capabilities, and continuously improve the company's AI ecosystem.

Success in this role comes from delivering reliable, scalable AI systems that help automate business operations and accelerate product development.