cognition - AI Support Engineer
Requirements
• 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. • 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. • EQUAL OPPORTUNITY
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.
Apply in one click
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT