AI Support Engineer
CognitionVisit Cognition website
Cognition is an applied AI company that operates Devin, an autonomous software-engineering agent.
San Francisco, United States
Funding history
About Cognition
Cognition builds AI agents and models for software engineering. Its flagship product, Devin, can plan, write, test, and ship code in a customer’s existing codebase and tools.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will investigate, reproduce, and resolve complex customer issues involving infrastructure, developer tooling, CI/CD systems, APIs, containers, and cloud platforms. You will analyze logs and code paths, escalate well-documented issues, educate customers, and improve support workflows through playbooks, tooling, automation, and documentation.
Requirements
- 4+ years of experience in software engineering, infrastructure engineering, solutions engineering, technical support engineering, or developer tooling
- Bachelor’s degree or higher in computer science, software engineering, or a related technical field, or equivalent practical experience
- Working knowledge of Linux, Docker, Git, CI/CD pipelines, cloud platforms, and networking fundamentals
- Ability to reproduce, isolate, and debug issues from incomplete or ambiguous reports
- Experience analyzing logs, traces, errors, and system behavior across distributed or multi-component systems
- Ability to read and reason about code in multiple languages such as Python, TypeScript, Java, or Go
- Strong written communication skills
- Ability to manage a steady stream of incoming issues with urgency
- Passion for AI and developer tools
Responsibilities
- Investigate, reproduce, and diagnose complex customer issues across development environments
- Perform root-cause analysis using logs, code paths, system behavior, and hypotheses
- Resolve incoming technical issues while communicating clearly with customers
- Escalate product or infrastructure issues with reproduction steps, logs, environment details, and root-cause hypotheses
- Educate customers on best practices, workarounds, deployment patterns, and product capabilities
- Build internal playbooks, tooling, automations, and documentation
- Identify recurring failure modes and share feedback with product, engineering, and deployment teams
- Support release testing and quality efforts across customer environments and workflows
