Support Engineer

Description

The company raised a $250M Series C led by a16z, with existing investors Benchmark, Lightspeed and YC also investing. The round puts the valuation at $2.2 billion.

The company builds a search engine for AI. Its Search API is used by agents, Fortune 500 companies and AI labs. The team is largely based in San Francisco, has about 100 people, and includes former founders, dropouts and people from Harvard, MIT, Meta and Google Research.

The team is high agency and low ego, and believes this is one of the last problems worth solving well.

Responsibilities

• Set up and configure the Pylon instance, including ticket tracking, SLA tracking and automations that keep support running efficiently.
• Troubleshoot tickets the AI cannot resolve across the API, SDKs and customer integrations.
• Reproduce bugs and fix them by opening pull requests that Engineering reviews.
• Escalate to Engineering when you cannot solve a problem yourself, with reproduction steps, logs, customer impact and what you have already ruled out.
• Stay the contact for every customer follow-up on your tickets, including escalated ones, until the issue is resolved.
• Improve docs, the knowledge base and the Pylon and agent workflows so more tickets get resolved without a person.
• End each shift with an automated handoff that gives the next Support Engineer full context on open tickets, keeping the follow-the-sun handoff tight.
• Keep the account team (Account Executives and Forward Deployed Engineers) informed about tickets from their accounts and flag account-level risk early.
• Monitor account health signals, mostly through AI. Raise every contraction or churn risk to the account team and leadership with requested actions and owners, and follow each one until it is resolved.
• Find patterns across tickets and turn them into product feedback and fixes.
• Support Engineers have the same technical depth as Forward Deployed Engineers and own the fix, not just follow a script.

Requirements

• Several years of hands-on programming experience, including reading and debugging unfamiliar code and opening pull requests in a production codebase.
• Experience troubleshooting APIs, SDKs or distributed systems in production. Experience with search, retrieval, LLMs or data pipelines is a plus.
• A structured way of working through ambiguous problems: you ask the right questions, form hypotheses and test them.
• Good judgment on when to keep digging and when to escalate, and the ability to explain technical problems clearly to customers and engineers.
• Comfort working AI-first, using AI tools and agents as part of your daily work.
• Available for shift work as part of a 24/7, follow-the-sun support model.
• Nice to have: you have worked as a software engineer, support engineer, solutions engineer or site reliability engineer at a developer-tools, API or AI company.
• Nice to have: you have built with LLMs, RAG or agents and can reason about retrieval and search quality.
• Nice to have: you have built automations or AI workflows that took repetitive work off a team.
• Nice to have: you enjoy being the person who works out what is going on.
• Nice to have: you care about organizing the world's knowledge and making it accessible to machines.

Conditions

This role is in person in San Francisco.

Support runs 24/7 on a follow-the-sun model, so shift work is required.

Benefits

• Premium healthcare covering medical, dental and vision.
• Fertility benefits.
• A monthly wellness stipend for all employees.