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Exa

Support Engineer

Exa is hiring a Support Engineer in San Francisco, United States. It pays $115k-$225k a year and Level rates it ; you can apply on Exa.

Level's read on this job

  • On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Tools and skills the posting cites include RAG.
  • Level lists 60 other open roles at Exa.
  • The role was posted in the last few days.

AI in this role

rag

About Exa

We raised a $250M Series C to build the search engine for AIs. Led by a16z, with existing investors Benchmark, Lightspeed, and YC doubling down, the round brings Exa's valuation to $2.2 billion.

Exa is building a search engine for the AI era. Our Search API currently powers Agents, Fortune 500s, and AI labs as we transform an industry that hasn't been disrupted since the 90s. We're a largely SF-based team of ~100 from Harvard, MIT, Meta, Google Research, ex-founders, and dropouts alike. We are rapidly building the most intelligent search engine in history. We're high agency, low-ego, and united by the feeling that this is one of the last problems worth getting right.

About the Role

Support Engineers make sure every committed Exa customer gets their problem solved, fast, around the clock. We run support AI-first: AI tools like Pylon and agents triage tickets, answer them and resolve what they can. You take on what the AI can't: the hard, ambiguous technical problems that need a real engineer.

You'll have the same technical depth as our Forward Deployed Engineers. You'll dig into the API, SDKs and customers' integrations, reproduce bugs, and open pull requests with fixes for our engineers to review. When a problem truly needs Engineering, you escalate it with everything they need to act, and you stay the customer's point of contact until it's resolved. This is not a script-reading role. You are an engineer who owns the fix.

In this role, you will:

  • Build the support system: configure our Pylon instance and set up robust ticket tracking, SLA tracking and automations that make the support function as efficient as possible

  • Resolve the tickets the AI can't, troubleshooting across the API, SDKs and customer integrations

  • Reproduce bugs and fix them, opening pull requests directly for Engineering to review

  • Escalate to Engineering with full context when you can't solve it yourself: reproduction steps, logs, customer impact and what you've already ruled out

  • Own every customer follow-up on your tickets, including escalated ones, until the issue is resolved

  • Make the AI first line better by improving docs, the knowledge base and our Pylon and agent workflows, so more tickets resolve without a human

  • Keep the follow-the-sun handoff tight: end each shift with an automated handoff that gives the next Support Engineer full context on open tickets

  • Work with the account team (Account Executives, Forward Deployed Engineers), keeping them informed on tickets from their accounts and flagging account-level risk early

  • Handle escalation management: watch account health signals, largely through AI, raise every contraction or churn risk to the account team and leadership with requested actions and owners, and follow it until resolved

  • Spot patterns across tickets and turn them into product feedback and fixes

Requirements

  • Several years of hands-on programming experience. You can read and debug unfamiliar code, and you're comfortable opening pull requests in a production codebase

  • Experience troubleshooting APIs, SDKs or distributed systems in production, ideally with search, retrieval, LLMs or data pipelines

  • A structured approach to ambiguous problems: you ask the right questions, form hypotheses and test them

  • Clear judgment on when to keep digging and when to escalate, and the ability to explain a technical problem clearly to customers and engineers

  • Comfort working AI-first, with AI tools and agents as part of your daily workflow

  • Availability for shift work as part of a 24/7, follow-the-sun support model

You might excel if you...

  • Have worked as a software engineer, support engineer, solutions engineer or site reliability engineer at a developer-tools, API or AI company

  • Have built with LLMs, RAG or agents, and can reason about retrieval and search quality

  • Have built automations or AI workflows that took repetitive work off a team

  • Like being the person who finally figures out what's going on

  • Care deeply about the problem of organizing the world's knowledge and making it accessible to machines

This an in-person opportunity in San Francisco. In addition to premium healthcare benefits (medical, dental, vision), we also offer fertility benefits and a monthly wellness stipend to all of our employees.

Exa is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, age, veteran status, marital status, pregnancy or related conditions, criminal histories consistent with applicable law, or any other basis protected by applicable law.

How we rate this

Support Engineer at Exa rates 74 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAG

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. Describe a typical day in a role like this one: which parts run through AI directly?
  3. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: RAG. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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