Cohere
AI Frontier · Enterprise LLMs
AI Frontier · Enterprise LLMs
Cohere has 77 active AI-related job listings. The majority of these roles are focused on agents, representing 39% of the total. Engineering is the dominant function, with 60 positions. The company is actively hiring for roles related to model serving, agent orchestration, and fine-tuning. In the last 30 days, Cohere has posted 17 new AI roles, a significant increase compared to the previous 30-day period.
Currently tracking 69 active AI roles, down 22% versus the prior 4 weeks. Primary focus: Agent · Engineering.
Cohere currently has 78 active AI-related roles in our index. The most common open titles are: Forward Deployed Engineer, Agentic Platform (2), Solutions Architect - Public Sector (2), Applied AI Engineer - Agentic Workflows (Singapore), Applied AI Engineer – Agentic Workflows, Applied AI Engineer – Agentic Workflows (Korea). Most positions are in Engineering and Research.
Cohere's active AI hiring is concentrated in: agents (36%), data (19%), serving infrastructure (18%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Cohere is hiring AI talent in: Canada (34 roles), United States (16 roles), United Kingdom (14 roles), France (3 roles).
Job postings at Cohere most frequently reference: model serving, agent orchestration, fine tuning, inference infra, rag.
In the past 30 days, Cohere has posted 9 new AI-related roles. That is a -40% change versus the prior 30 days (15 → 9).
| Title | Stage | AI score |
|---|---|---|
| Member of Technical Staff, Training Infra Engineer Cohere is seeking a Member of Technical Staff, Training Infra Engineer to design and write high-performant and scalable software for model training. This role will improve training setup, craft tools to speed up training cycles, and research/implement ideas on supercompute and data infrastructure. The ideal candidate has strong software engineering skills, proficiency in Python and ML frameworks like JAX/PyTorch, and experience with distributed training infrastructures and large-scale distributed training strategies. | DataPretrain | 9 |