AI Agent Builder

We’re looking for a highly technical, systems-minded AI Agent Builder who can design, deploy, and orchestrate autonomous AI agent swarms using tools like OpenClaw and similar agent frameworks.

This is not a prompt engineering role. We are looking for someone who understands multi-agent architectures, task decomposition, memory management, orchestration layers, and how agents communicate, coordinate, and self-correct inside production environments.

You should be capable of building agent systems that operate reliably across workflows such as research, automation, content generation, customer operations, or internal tooling. This role requires deep practical experience building and deploying agents, not experimenting with them casually.

This role requires full alignment with US working hours.

Why You’ll Want to Join

• You will be paid in USD (bi-monthly: every 15th and 30th)
• Up to 14 days of Paid Time Off annually (starting Day 1)
• Observance of Holidays per company guidelines
• 100% remote setup so you can work wherever you’re most productive
• High-ownership role designing autonomous AI systems
• Opportunity to build real-world agent infrastructure from the ground up
• Direct collaboration with technical leadership on AI architecture

What You’ll Work On

Multi-Agent System Architecture

• Design and build multi-agent swarms using OpenClaw or similar orchestration frameworks
• Define agent roles, communication patterns, and execution hierarchies
• Implement task delegation, coordination logic, and fallback systems
• Architect agent collaboration models that scale across workflows

Agent Orchestration and Infrastructure

• Build orchestration layers that manage agent state, memory, and context persistence
• Design systems for logging, monitoring, and debugging agent behavior
• Integrate agents with APIs, databases, and internal tools
• Ensure reliability and guardrails in autonomous execution

Workflow Automation and AI Systems

• Translate business workflows into agent-driven execution pipelines
• Build autonomous research agents, execution agents, validation agents, or hybrid swarms
• Optimize token usage, latency, and performance across multi-agent systems
• Improve system reliability through iteration and structured testing

AI Engineering and Tooling

• Work with LLM APIs and model orchestration frameworks
• Implement memory systems including vector stores or structured state layers
• Use AI-native development workflows and coding copilots effectively
• Continuously improve agent reasoning and coordination strategies

What You Bring

• 4+ years of software engineering experience
• Direct experience building and deploying multi-agent systems
• Hands-on experience using OpenClaw or comparable agent orchestration frameworks
• Strong understanding of LLM behavior, prompt structuring, and agent coordination
• Experience integrating agents with production systems and APIs
• Strong system design fundamentals including distributed systems and data flows
• Ability to work autonomously in fast-moving startup environments
• Comfort working during US business hours

Preferred but not strictly required:

• Experience with vector databases and embeddings
• Background in AI automation or workflow orchestration systems
• Experience building internal AI infrastructure
• Familiarity with cloud infrastructure such as AWS or GCP

Nice to Have

• Experience building large-scale autonomous agent swarms
• Exposure to reinforcement learning or evaluation pipelines
• Experience implementing monitoring and observability for AI systems
• Prior experience in AI-first or automation-driven startups

How to Apply

Please include:

1. Your updated resume
2. A short 1 to 2 minute Loom video describing an agent-based system you built, including how you structured agent coordination, memory, and orchestration

Only complete applications with a Loom video will be considered.

If you are a systems-oriented engineer who understands how to design autonomous agent swarms, orchestrate intelligent workflows, and build reliable AI infrastructure, this role offers meaningful ownership and the opportunity to shape next-generation AI systems.

Application Process Overview

Our comprehensive selection process ensures we find the right fit for both you and our clients:

1. Initial Application - Submit your application and complete our prequalifying questions
2. Video Introduction - Record an video introduction to showcase your communication skills and work experience
3. Role-Specific Assessment - Complete a homework assignment tailored to the position (if applicable)
4. Recruitment Interview - Initial screening with our talent team
5. Executive Interview - Meet with senior leadership to discuss role alignment
6. Client Interview - Final interview with the client team you'd be supporting
7. Background & Reference Check - Professional reference verification
8. Job Offer - Successful candidates receive a formal offer to join the team

Each stage is designed to evaluate your fit for the role while giving you insights into our company culture and expectations. We'll keep you informed throughout the process and provide feedback at each step.