Cognition
Coding AI · Devin autonomous coding agent
Currently tracking 13 active AI roles, down 27% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $260k–$300k (avg $280k).
Cognition currently has 22 active AI-related job listings, with a significant focus on roles within the "agents" stage, accounting for 64% of their openings. The majority of these positions are in Engineering. The company is actively hiring for roles related to agent orchestration, LLM observability, and tool use.
Coding AI · Devin autonomous coding agent
Cognition currently has 24 active AI-related roles in our index. The most common open titles are: Partner Deployed Engineer - APAC (2), AI Enablement Engineer, AI Support Engineer, Applied AI Engineer - ANZ, Applied AI Engineer - APAC. Most positions are in Engineering and Product.
Cognition's active AI hiring is concentrated in: agents (67%), application (21%), serving infrastructure (4%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Cognition is hiring AI talent in: United States (13 roles), United Kingdom (2 roles), Singapore (2 roles), Japan (2 roles).
Job postings at Cognition most frequently mention: CI/CD, System Design, Kubernetes, Tool-Using Agents, Technical Leadership.
In the past 30 days, Cognition has posted 5 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Deployed Engineer, Federal Applied AI lab building end-to-end software agents, specifically Devin (AI software engineer) and Windsurf (AI-native IDE). This role is for a foundational engineer in the federal group, focusing on deploying and integrating these agents within federal enterprise accounts, translating customer needs into product requirements, and architecting complex deployments. | Ship | 7 |
| Deployed Engineer This role is for a Deployed Engineer at an applied AI lab building end-to-end software agents like Devin and Windsurf. The engineer will be customer-facing, helping customers maximize value from the AI agents by understanding workflows, identifying use cases, deploying into production, supporting integrations, and driving adoption. The role requires a strong engineering foundation, customer empathy, ownership, technical curiosity, bias towards execution, grit, and exploratory rigor. It involves hands-on technical work, customer partnership, and rapid execution in ambiguous, high-intensity environments. |
| Ship |
| 5 |