Remote RL Environment Engineer for Enterprise AI

Cohere; Greater London; Remote; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Weekly lunch stipend

Health and dental benefits

RRSP matching / Pension

Parental Leave top-up

Education stipend

6 weeks paid vacation

Travel budget to other offices

Home office stipend

Job summary

Cohere is seeking an experienced RL environment engineer to create scalable environments for enterprise AI agents and to run agents inside them, improving both agents and environments.

You will collaborate across modeling and product to identify gaps in agent performance, work with external vendors to build high-quality RL environments, and help automate evaluation and training workflows. You will shape input data, verifiers, and benchmarks to drive rapid, data-informed improvements.

Qualifications

• You may be a good fit if you have engineered agents and optimized them for specific industry use cases.
• You have spent dozens of hours reviewing agent trajectories to pinpoint exact failure points and fix them with model training or harness engineering.
• You obsess over measuring agentic capabilities and turning that into a repeatable process.
• You have had debates about what a good outcome from an AI agent should look like, translated into verifier implementations and tuned rewards.
• You have designed and run annotation workflows to surface insights into agent performance and verify data quality.
• You have built synthetic data pipelines to scale eval and training.

Responsibilities

• Build new RL environments targeting different agentic capabilities and industry areas
• Train and evaluate agents in those environments
• Make all the pieces work together: tasks, data, tool implementations, and verifiers
• Work across modeling and product to identify gaps in agent performance, and improve both the agents and the environments
• Work with external vendors to create high-quality, expert-built RL environments, and build tools to ensure high task, data, and verifier quality
• Automate the discovery of model capability gaps, and systematically measure agent performance during evals and training

Skills

Agent engineering

RL environment design

Agent evaluation

Data quality verification

Annotation workflows

Synthetic data pipelines

Performance measurement

Rapid experimentation

Job description

Cohere is seeking an experienced RL environment engineer to create scalable environments for enterprise AI agents and to run agents inside them, improving both agents and environments.

You will collaborate across modeling and product to identify gaps in agent performance, work with external vendors to build high-quality RL environments, and help automate evaluation and training workflows. You will shape input data, verifiers, and benchmarks to drive rapid, data-informed improvements.