RL Environments Engineer — Build Deterministic Agent Sandboxes

Fdetimes; San Francisco (CA); On-site; USD 140,000 - 200,000; Full time

Job summary

Labelbox is seeking a Forward Deployed Engineer to design, develop, and operationalize reinforcement learning environments. You’ll build sandboxed, reproducible environments that AI agents interact with during training and evaluation, delivering robust, observable infrastructure for team use.

You’ll write production-grade infrastructure code and integrate with open-source RL tooling, collaborating with data operations to ensure environments are reliable for human annotators and model agents

Qualifications

• 2+ years of professional software engineering experience.
• Strong Python and at least one systems language (Go/Rust/C++)
• Experience with containerization and sandboxing (Docker, Podman, Firecracker, or similar) in production or near-production contexts
• Familiarity with RL concepts: MDPs, reward shaping, episode structure, observation/action spaces
• Experience building or maintaining developer tooling, CLI tools, or infrastructure automation
• Comfort working with browser automation frameworks or terminal interaction tooling
• Strong debugging instincts—you can trace failures across process boundaries, container layers, and network calls

Responsibilities

• Design, build, and maintain sandboxed RL environments for agentic AI training.
• Develop reproducible, containerized execution environments (Docker, VMs, lightweight sandboxes) that support deterministic task rollouts and reward signal collection
• Integrate with and extend open-source agentic tooling and custom CLI/API harnesses to enable multi-step agent interaction
• Build instrumentation and observability layers - structured logging, trajectory capture, state snapshotting
• Collaborate with data operations to design task curricula and evaluation protocols
• Own environment deployment and reliability: CI/CD pipelines, automated testing of environment configurations, and monitoring for drift or breakage across versions
• Rapidly prototype new environment types as client and internal requirements evolve

Skills

Python

Go

Rust

C++

Debugger skills

CI/CD

Tools

Docker

Virtual Machines

Kubernetes

Job description

Labelbox is seeking a Forward Deployed Engineer to design, develop, and operationalize reinforcement learning environments. You’ll build sandboxed, reproducible environments that AI agents interact with during training and evaluation, delivering robust, observable infrastructure for team use.

You’ll write production-grade infrastructure code and integrate with open-source RL tooling, collaborating with data operations to ensure environments are reliable for human annotators and model agents