AI Support Engineer

We're the makers of Devin, the first AI software engineer, and Windsurf, the AI-native IDE. Together, they represent our vision for collaborative AI teammates that enable engineers to focus on more interesting problems and empower teams to strive for more ambitious goals.

Our team is small and talent-dense. Among our founding team, we have world-class competitive programmers, former founders, and leaders from companies at the cutting edge of AI including Scale AI, Palantir, Cursor, Waymo, Tesla, Lunchclub, Modal, Google DeepMind, and Nuro.

Building Devin and Windsurf is just the first step—our hardest challenges still lie ahead. If you’re excited to solve some of the world’s biggest problems and build AI that can reason on real-world tasks, apply to join us.

About the Role

Cognition is building the AI software engineer of the future. As an AI Support Engineer, you will be responsible for resolving complex technical issues for customers using Devin and Windsurf in real-world development environments.

This role goes well beyond basic support. You will investigate ambiguous, environment-specific problems across codebases, infrastructure, developer tooling, CI/CD systems, APIs, containers, and cloud platforms. You will reproduce bugs, analyze logs, trace failures, form root-cause hypotheses, and drive issues to resolution quickly and rigorously.

We are looking for someone with strong debugging instincts, broad systems knowledge, and the ability to operate with urgency across a high volume of technical issues. You should be comfortable context-switching across problem domains, communicating clearly with customers, and partnering closely with engineering when deeper product investigation is required.

This is a unique opportunity to work at the frontier of AI-assisted software development, with real customers relying on the product every day.

Responsibilities

• Investigate, reproduce, and diagnose complex customer issues across diverse development environments, including cloud infrastructure, CI/CD systems, APIs, containers, version control, IDEs, and enterprise deployment setups.

• Perform root-cause analysis by reading logs, tracing code paths, correlating system behavior, forming hypotheses, and isolating failures.

• Resolve a high volume of incoming technical issues while maintaining strong investigation quality and clear customer communication.

• Escalate product or infrastructure issues to engineering with complete technical context, including reproduction steps, logs, environment details, and root-cause hypotheses.

• Educate customers on best practices, workarounds, deployment patterns, and product capabilities to improve adoption and reduce recurring issues.

• Build internal playbooks, tooling, automations, and documentation that make future investigations faster and more systematic.

• Identify recurring failure modes and share actionable feedback with product, engineering, and deployment teams.

• Support release testing and quality efforts across the range of environments, languages, IDEs, and workflows our customers use.

Qualifications

• 4+ years of experience in a technical role such as 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 such as AWS/GCP/Azure, and networking fundamentals.

• Demonstrated ability to reproduce, isolate, and debug technical issues from incomplete or ambiguous reports.

• Experience analyzing logs, traces, errors, and system behavior across distributed or multi-component systems.

• Strong ability to read and reason about code in multiple languages, such as Python, TypeScript, Java, Go, or similar.

• Strong written communication skills, especially when explaining technical findings to customers and internal engineering teams.

• Ability to operate with urgency in a fast-paced environment while managing a steady stream of incoming issues.

• Passion for AI, developer tools, and the future of software engineering.

Nice to Have

• Experience building internal tools, scripts, or automations to accelerate debugging, support, or QA workflows.

• Familiarity with LLMs, AI-assisted development tools, IDEs, or developer productivity platforms.

• Experience in high-volume technical support or customer engineering environments.

• Experience debugging issues that span multiple layers of the stack, such as application logic, infrastructure, authentication, third-party APIs, networking, or deployment configuration.

• Prior experience working directly with engineering teams to escalate, diagnose, and resolve product issues.