Cognition
Coding AI · Devin autonomous coding agent
Coding AI · Devin autonomous coding agent
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.
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 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 |
|---|---|---|
| Partner Deployed Engineer - APAC This role focuses on enabling Global Systems Integrators (GSIs) to deploy, scale, and deliver value with Cognition's AI agents (Devin and Windsurf) to their clients. The Partner Deployed Engineer will work closely with partners to build repeatable offerings, provide technical enablement, co-deliver pilots, and act as a technical representative within partner organizations, influencing the product roadmap based on field learnings. | Ship | 8 |
| 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 - LATAM This role is for a Deployed Engineer at an applied AI lab that builds end-to-end software agents, specifically focusing on their product Devin, the first AI software engineer. The engineer will be customer-facing, helping customers maximize value from Devin by understanding their workflows, identifying use cases, deploying Devin into production, leading demos, supporting integrations, and driving adoption. The role involves hands-on technical work, customer partnership, and rapid execution in a high-intensity, ambiguous environment. The engineer will also contribute to product development by implementing requested features and advocating for customer needs. | Ship | 5 |
| QA Engineer - APAC QA Engineer role focused on ensuring the quality of AI software agents (like Devin and Windsurf) by owning end-to-end product quality, designing and executing test strategies, debugging issues across layers (including AI behavior), and building scalable QA processes and automation. Requires strong QA experience, a developer mindset, and familiarity with AI-powered products. | Ship | 5 |
| Data Engineer, GTM & Product This role is for a Data Engineer at an applied AI lab building end-to-end software agents like Devin, the AI software engineer, and Windsurf, the AI-native IDE. The engineer will own the full data stack, including database architecture, pipelines, integrations, and reporting, with a focus on product and GTM reporting. The goal is to ensure data is reliable, accessible, and actionable. | Ship | 5 |
| 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 |