Ability to understand the complete Support App architecture to determine if an error originates from the core platform, a snap-in, or a customer's configuration.
Help in resolving highly complex and escalated customer queries transferred by junior support engineers.
Identify potentially problematic services, check for recent code commits, and perform a rollback if the root cause is confirmed.
Device plans to continuously upskill junior support engineers.
For issues in snap-ins or configurations, a deep understanding of how they work is required to check for recent changes. This includes reasoning about workflows, agents, customisations, analytics, and portals to identify misconfigurations.
Basic knowledge of Kubernetes (k8s) and AWS infrastructure to debug and reason about infrastructure-level failures.
Exposure to building LOG monitoring dashboards and alerts.
Act as a champion in highlighting the repetitive pain points of customers and devise a solution to stop them from re-surfacing.
Help in triaging and resolving critical BUGS, features, and custom requests reported by DevRev customers.
Requirements :
Experience : 3-6 years.
Master's degree in Computer Science or related field / equivalent practical experience.
Excellent logical thinking and problem-solving mindset.
The ability to expertly use observability tools by reading logs, analysing traces, and interpreting metrics to pinpoint issues.
Proficiency in reading and understanding Golang, JavaScript (JS), and Python to trace issues through different parts of the codebase.
Deep knowledge of the product's features and the underlying engineering architecture is essential for effective debugging.
Skillfully using tools to inspect and debug API calls between the application and its various integrations.
Methodically isolating problematic components, whether it's a microservice, a database query, or a third-party integration.
Basic knowledge of Kubernetes (k8s) and AWS infrastructure
Familiarity with Cursor or similar investigation tools for live or near-real-time monitoring.
Comfortable with GitHub workflows, including branching, PR reviews, and GitHub best practices.
Strong testing mindset, with experience in writing and executing test cases and verifying hotfixes in production-like environments.
Experience in sprint management, stakeholder communication, and working cross-functionally with engineering and product teams.
Nice-to-Have :
Prior experience supporting or working on Agentic AI systems, LLMs, or AI copilots.
Familiarity with CI / CD workflows and build tools.
Exposure to customer support systems and experience collaborating with different cross-functional teams.
Ability to generate actionable insights from logs and telemetry data.