AI Systems Engineer (Multi-Agent Orchestration)
Engineering Role Details
Posted Apr 06, 2026At TeamStation AI, we are on a mission to bring together the brightest minds to solve tomorrow’s toughest technology challenges. Our work is about more than just AI—it’s about building the future through collaboration and innovation. We believe that the key to solving the world’s most complex problems lies in aligning diverse talents and perspectives. Our AI-powered platform enables cutting-edge scientific and technical teams to work smarter, faster, and together. By joining us, you’ll help unlock new technological breakthroughs and drive innovation where it matters most.
Join the Mission at TeamStation AI!
Where do we come from? We are seeking visionaries, innovators, and problem solvers who thrive in fast-paced, collaborative environments. If you’re passionate about AI, technology, and solving critical challenges, we want to hear from you. Come be part of a team where your ideas can drive the future.
AI Systems Engineer (Multi-Agent Orchestration)
Location: Remote - LATAM
Type: Full-time
Reports to: CTO / Head of Engineering
Role Overview
We are seeking an AI Systems Engineer to design, orchestrate, and scale multi-agent development workflows using modern AI coding runtimes and orchestration platforms such as Gastown.
This role focuses on coordinating autonomous coding agents, maintaining persistent workflow state, and building reliable, reproducible engineering pipelines. The ideal candidate thinks in systems, automates relentlessly, and thrives at the intersection of AI-assisted development, DevOps, and distributed systems.
You will transform AI coding tools from isolated assistants into a coordinated engineering workforce.
What You Will Do
Multi-Agent Workflow Orchestration
- Design and manage multi-agent development workflows
- Coordinate agent task distribution, handoffs, and lifecycle management
- Maintain persistent work state and recovery workflows
AI Development Pipeline Engineering
- Integrate AI runtimes (Claude Code, Codex, Cursor, etc.) into structured workflows
- Build reproducible task pipelines using git-backed persistence and automation hooks
- Monitor agent performance, throughput, and reliability
Systems & Automation
- Implement workflow automation and fault-tolerant execution patterns
- Design task queues, coordination logic, and recovery strategies
- Optimize developer velocity through orchestration and tooling
Developer Experience & Tooling
- Create tooling that improves visibility into agent work and system state
- Document workflows and operational patterns
- Improve reliability, observability, and auditability of AI-assisted development
Required Qualifications
- 5+ years software engineering experience
- Strong Git and CLI workflow proficiency
- Experience with automation, CI/CD, or DevOps tooling
- Understanding of distributed systems or task orchestration concepts
- Experience using AI coding tools in real development workflows
- Strong systems thinking and debugging skills
Preferred Experience
- Experience with multi-agent orchestration tools (Gastown or similar)
- Background in DevOps, platform engineering, or SRE
- Experience designing developer productivity tooling
- Familiarity with tmux, shell scripting, and automation pipelines
- Experience integrating LLM APIs or AI runtimes into workflows
What Success Looks Like
- AI agents execute work reliably and reproducibly
- Development throughput increases without coordination chaos
- Work state persists across sessions and failures
- Engineering workflows become observable, auditable, and scalable
- Human engineers focus on architecture and decisions, not task micromanagement
Who Thrives in This Role
You enjoy:
- designing systems rather than manual processes
- automating repetitive coordination work
- turning chaos into structured pipelines
- building tools that multiply engineering output
You think like a systems engineer and operate like a builder.
Why This Role Matters
Software engineering is evolving from writing code to orchestrating intelligent systems that produce it. This role sits at the frontier of that shift.
You will help define how modern engineering teams scale cognition, not just code.