Senior RL Environments Engineer

Lumos AI Research; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Lumos AI Research in San Francisco seeks a Senior Software Engineer to build high‑fidelity RL environments and sandboxes that enable frontier AI agents to interact with software, APIs, and laboratory tools. You’ll own end‑to‑end architecture from environment design to deployment and evaluation, ensuring reproducibility and scalable execution.

You’ll collaborate with wet‑lab engineers and researchers to connect AI agents to physical experiments, robotics, and automation, translating real

Qualifications

• 5+ years of software engineering experience, or equivalent evidence of exceptional engineering ability.
• Excellent Python skills and strong fundamentals in algorithms, data structures, systems design, and software architecture.
• Hands-on experience with Docker, Linux, containers, process isolation, or sandbox execution.
• Strong understanding of distributed systems, asynchronous execution, state management, and reliability.
• Experience designing complex APIs, backend systems, and integrations.
• Ability to independently architect, build, debug, and ship sophisticated technical systems.

Responsibilities

• Build RL environments: Design and implement realistic, stateful environments that reproduce complex workflows across healthcare, biology, and scientific software.
• Develop secure sandboxes: Build isolated, reproducible execution environments supporting agent-generated code, tool calls, filesystem operations, and application interactions.
• Connect AI agents to the wet lab: Work with scientists and automation engineers to integrate laboratory instruments, robotic liquid handlers, experimental protocols, and biological readouts into agent-accessible workflows.
• Build agent-facing tools: Implement MCP servers, APIs, and interfaces that enable agents to interact with software applications, scientific instruments, and simulated systems.
• Engineer state management: Develop deterministic initialization, snapshot/restore, state transitions, resets, and execution replay.
• Develop tasks and verifiers: Translate real-world workflows into executable tasks with clear success criteria, ground-truth states, and programmatic verification.
• Scale environment execution: Build orchestration infrastructure for high-throughput parallel rollouts, supporting both simulated environments and physical experiments with appropriate execution controls.
• Work with Harbor: Develop, integrate, and validate environments using Harbor-compatible task structures, execution harnesses, and evaluation workflows.
• Improve environment fidelity: Identify unrealistic shortcuts, hidden state inconsistencies, and verification gaps that could compromise training quality.
• Own the full lifecycle: Take ambitious technical ideas from early prototypes through production-grade infrastructure.

Skills

Python

Algorithms

Data structures

Systems design

Software architecture

Distributed systems

APIs

Backend systems

Tools

Docker

Linux

Harbor

Gymnasium

Ray

Job description

Lumos AI Research in San Francisco seeks a Senior Software Engineer to build high‑fidelity RL environments and sandboxes that enable frontier AI agents to interact with software, APIs, and laboratory tools. You’ll own end‑to‑end architecture from environment design to deployment and evaluation, ensuring reproducibility and scalable execution.

You’ll collaborate with wet‑lab engineers and researchers to connect AI agents to physical experiments, robotics, and automation, translating real