Technical Support Engineer

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Deep-Dive Debugging: Perform root-cause analysis on complex issues and distributed tracing gaps across polyglot environments.
Support the Great Minds: Act as a strategic consultant for senior engineers at our largest enterprise customers, solving high-stakes architectural challenges that push the boundaries of observability.
Troubleshoot SDK Implementations: Go deep into the source code of Sentry’s SDKs to help developers instrument complex frameworks and custom environments.
Engineering Feedback Loop: Serve as the bridge between the world's best developers and our product teams, using data from your systems to prioritize high-impact platform fixes.

Deterministic Support Paths: Engineer the logic that powers our support agents, moving beyond probabilistic guesses to high-fidelity, autonomous resolutions.
Knowledge Engineering: Build the right context into our systems so they can resolve issues consistently and indefinitely.
Agentic Tooling Development: Use MCP (Model Context Protocol) and Sentry’s internal APIs to build "skills" for our agents, allowing them to perform complex lookups or state-checks autonomously.
The Seer Philosophy: We’ve already proven AI can handle autonomous production fixes with Seer. You will apply that same philosophy to the support lifecycle—moving us from a "Help Desk" to an "Autonomous Resolution Engine."

You love eliminating Non-scalable effort: you enjoy automating repetitive work and take pride in building systems that save time and effort.
You’re a Full-Stack Troubleshooter: You enjoy jumping from a React frontend issue to a Python backend trace to a CI/CD pipeline failure in a single afternoon
You Value Evidence-Based Support: You prefer looking at data trends over anecdotal evidence to decide where to build automation next.
You’re a Developer Advocate: You want to guide the industry on how elite engineers and AI co-exist in a high-density technical ecosystem.

4+ years of experience in technical support engineering, systems engineering, or software development, with a track record of solving high-complexity SaaS problems.
Strong Coding Foundations: Mastery of Python, JavaScript, Java, or Ruby. You are comfortable reading SDK source code and identifying bugs in production-level repositories.
Systems Depth: Deep understanding of distributed systems, microservices, APIs, and the "path of a pixel" from frontend to database.
AI & Automation Literacy: Practical familiarity with LLM orchestration (RAG, context windows, system prompts) and a critical eye for where AI succeeds versus where it requires human intervention.
Exceptional Communication: The ability to explain complex architectural concepts to a human and write precise "system instructions" for an AI.

Open Source Contributor: An active presence on GitHub or experience maintaining open-source libraries.
Former Software Developer: You’ve spent time in the trenches as a full-time dev and know exactly what keeps our customers up at night.

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