The posting
Role Summary:
We are seeking an AI Systems Engineer to build the reliable software infrastructure that connects models, applications, external tools, and real-world systems. This role is for someone who enjoys turning AI prototypes into reliable, observable, and maintainable systems.
Location: Hollywood, FL (or willing to relocate)
What You'll Do:
- Design runtimes and services around remote, streaming, or action-sequence model inference.
- Handle latency variation, stale outputs, retries, partial failures, service outages, and safe shutdown.
- Build interfaces that support different model providers, architectures, data sources, and downstream systems.
- Integrate inference clients, state and sensor inputs, task scheduling, observability, and safety or authorization checks.
- Build agentic loops and tool-using systems with clear permission boundaries, structured outputs, human approval paths, and MCP-compatible interfaces.
- Reproduce failures using deterministic tests, logs, traces, recorded-data replay, and fault injection.
- Take prototypes through reliable, observable, and maintainable deployment.
Must-Haves:
- Strong software architecture, concurrency, networking, debugging, testing, and production-reliability skills.
- Experience with agentic systems, tool-use loops, MCP practices, distributed systems, inference infrastructure, or real-time applications.
- Programming language flexibility (Python experience is helpful but not strictly required).
Nice-to-Haves:
- Robotics experience (integration with cameras, robot state, controllers, action scheduling, simulation, or physical hardware). Note: This is a preferred signal rather than a hard requirement.
- Experience with ROS or ROS 2, Gazebo, MoveIt, URDF, Xacro, TF2, RViz, rosbag, MCAP, or related robotics tooling.



