Tavily

Technology

TechnicalSupportEngineer

€45–65k ~AI est. France FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Technical Support Engineer at Tavily. Skills: Technical support, LLM applications, Cloud environments. Monitor incoming tickets. Respond to incoming tickets”

What You'll Achieve.

Fast resolution; High-quality user experience

Industry & Context.

Technology
Problems you'll solve

Troubleshooting; Problem resolution

Eligibility Requirements

Occasional off-hours coverage

What They're Looking For.

Must Have

2+ years technical support experience, 2+ years customer engineering experience, Troubleshooting skills across APIs, Troubleshooting skills across backend systems, Troubleshooting skills across web applications, Troubleshooting skills across distributed infrastructure, Hands-on Python experience, Hands-on backend tooling experience, Familiarity with API debugging, Familiarity with integration workflows, Experience working with logs, Experience working with monitoring systems, Experience debugging production issues, Ability to work with third-party integrations, Ability to understand complex system dependencies, Written communication skills, Verbal communication skills, Ability to learn new technologies, Ability to adapt in fast-changing environments

Nice to Have

Experience with LangChain, Experience with LlamaIndex, Experience with vector databases, Experience with AI tooling ecosystems

What You'll Do.

Monitor incoming tickets

Respond to incoming tickets

Provide troubleshooting for API issues

Provide troubleshooting for product issues

Provide troubleshooting for deployment issues

Diagnose customer issues

Resolve customer issues

Support global customers

Collaborate with engineering

Collaborate with product

Collaborate with documentation

Collaborate with customer success

Improve internal tools

Use diagnostics systems

Improve diagnostics systems

Participate in incident post-mortems

Contribute to reliability improvements

Track support performance metrics

Contribute to continuous improvement

Improve knowledge base articles

Maintain knowledge base articles

Improve documentation

Maintain documentation

Influence product improvements

Influence engineering improvements

How You'll Work.

Team & Collaboration

Engineering teams; Product teams; Documentation teams; Customer success teams

Communication Scope

Explain technical issues

Full Job Description

## Accountabilities Monitor and respond to incoming technical support tickets, providing timely and accurate troubleshooting for API, product, and deployment-related issues. Diagnose and resolve customer issues across LLM applications, integrations, and cloud environments, escalating complex cases to engineering when needed. Support global customers through follow-the-sun coverage, ensuring continuity and responsiveness across time zones. Collaborate closely with engineering, product, documentation, and customer success teams to investigate bugs and deliver resolutions. Use and improve internal tools, runbooks, and diagnostics systems to enhance issue triage and support efficiency. Participate in incident post-mortems, documenting root causes and contributing to long-term reliability improvements. Track support performance metrics such as CSAT, resolution time, and recurring issues, contributing to continuous improvement efforts. Improve and maintain knowledge base articles and documentation to strengthen self-service capabilities for users. Provide feedback from customer interactions to influence product and engineering improvements. Contribute to a high-ownership support culture focused on fast resolution and high-quality user experience. Requirements 2+ years of experience in technical support, customer engineering, or similar roles in SaaS, developer tools, or cloud environments. Strong troubleshooting skills across APIs, backend systems, web applications, and distributed infrastructure. Hands-on experience with Python and backend tooling, with familiarity in API debugging and integration workflows. Understanding of LLM ecosystems, including concepts such as Retrieval-Augmented Generation (RAG), prompt engineering, and agent-based systems. Familiarity with tools and frameworks such as LangChain, LlamaIndex, vector databases, or similar AI tooling ecosystems. Experience working with logs, monitoring systems, and debugging production issues in real-world environme

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