Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading applied AI organization is building end-to-end software agents designed to perform real-world software engineering tasks. Its products include AI-powered software engineering and developer productivity tools, with a focus on developing AI systems capable of reasoning through complex technical problems.
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 reviewing logs, tracing code paths, correlating system behavior, developing hypotheses, and isolating failures.
- Resolve a high volume of incoming technical issues while maintaining strong investigation quality and clear customer communication.
- Escalate product and infrastructure issues to engineering teams 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.
- Develop internal playbooks, tooling, automations, and documentation to make future investigations faster and more systematic.
- Identify recurring failure patterns and provide actionable feedback to product, engineering, and deployment teams.
- Support release testing and quality initiatives across the various environments, programming languages, IDEs, and workflows used by customers.
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, or Azure, and networking fundamentals.
- Demonstrated ability to reproduce, isolate, and debug technical issues based on 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 programming languages, such as Python, TypeScript, Java, Go, or similar languages.
- Strong written communication skills, particularly 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 technical 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, technical support, or QA workflows.
- Familiarity with LLMs, AI-assisted development tools, IDEs, or developer productivity platforms.
- Experience working in high-volume technical support or customer engineering environments.
- Experience debugging issues spanning multiple layers of the technology stack, including 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.
Disclaimer
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- No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
- No Client Relationship: This company is not a client of SpringCube unless stated.
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