Sr. Software Engineer, Multiagent Simulation

About the role

Page Title: Sr. Software Engineer, Multiagent Simulation

FieldAI builds AI that allows robots to understand and operate in the real world. The company maintains a primary research and development center in Boston. There, the team creates systems that are risk-aware, reliable, and ready for field deployment. The goal is to solve the most difficult challenges in robotics and to expand the capabilities of embodied intelligence. FieldAI blends advanced research with real-world testing. The organization rejects strictly theoretical approaches in favor of practical results. Continuous improvement comes from rapid iteration based on real field data.

FieldAI is currently hiring for a position focused on multi-robot systems. The role is centered on simulation and the coordination of robot fleets. The successful candidate will work with a small, dedicated team. The environment is fast-paced and requires high-quality output. You will create virtual worlds where robots can operate together. These worlds must reflect realistic conditions and operational constraints. The position supports the development of fleet orchestration strategies. These strategies are tested and validated within the simulation before any field deployment. The ideal candidate understands robotics simulation deeply. You must also grasp the fundamentals of multi-agent systems. Practical coding skills are essential for long-term success in this role.

This position is located in Boston, Massachusetts. It is a full-time engagement. The compensation for this role is 180,000 USD annually.

You are responsible for the entire lifecycle of multi-agent behavior inside virtual environments. Your work defines how simulated robots perceive their surroundings, make plans, and interact with one another. You translate high-level fleet orchestration concepts into functional software. This code must be robust enough for testing and debugging. It must also be maintainable for future development. Collaboration is central to this position. You will work closely with research and deployment teams. This partnership ensures that simulation results remain honest. The results must always connect back to conditions found in the field.

Responsibilities

You will design intake pipelines for complex robotic data. These pipelines must handle robot models, scene definitions, and orchestration parameters. The goal is to generate coherent and consistent scenarios. You will craft core simulation components from the ground up. This includes physics abstractions that are efficient and scalable. You will define motion primitives that allow for precise control. You will also model communication protocols between agents. These building blocks must function well as the fleet scales.

You will establish formal review checkpoints for every simulation. These checkpoints will evaluate correctness and stability. They will also measure edge case coverage. Only after passing these reviews can assets be promoted. You will own the creation of shipping artifacts. These include configuration bundles and scenario packs. Downstream teams will use these to validate control strategies. You will partner with perception and planning groups. This alignment ensures realistic environment interactions. Interface contracts must be clear and consistent.

You will refactor existing data ingestion workflows. This work will handle heterogeneous data sources. Traceability is critical. You must preserve the link from raw logs to final simulation cases. You will guide architectural choices for multi-agent coordination. The representations you choose must remain understandable. Clarity is essential as fleet complexity increases. You will champion the scenario lifecycle. This covers creation, validation, retirement, and versioning. These practices apply to simulation assets used in production.

Qualifications

You must have three to five years of professional experience. Your background should be in robotic software or simulation components. You need a strong grasp of multiagent fundamentals. This includes coordination strategies and communication patterns. You must understand conflict resolution in shared workspaces. Practical coding skills are non-negotiable. You should write maintainable code in common languages. Your modules must have clear boundaries. Comprehensive test coverage is required.

You must be comfortable with robot description formats. Experience with sensor configuration files is mandatory. These formats are used in real field deployments. No specific additional skills or tools are listed for this role. There is no separate section for nice-to-have qualifications.

What you'll do

• Meet the bar Software Engineer, Multiagent Simulation.