Sierra Agent Engineer Interview Guide

Sierra is a rapidly growing AI startup focused on AI agents and autonomous LLM tools deployed by companies to handle customer interactions.

It was founded in 2023 and currently employs 500 people across offices in San Francisco, Atlanta, New York, and London.

Their agent engineer interview process combines technical skills with front-end and product sense decision-making, a blend that reflects the diverse responsibilities of agent engineers.

Below, we break down the complete agent engineer interview process at Sierra for junior and senior candidates.

Interview Process

Sierra’s Software Engineer Interview process goes through the following stages:

1. Recruiter/manager screen: High-level 30-minute interview with a recruiter to discuss the role, company, and your experience
2. Technical phone screen(s): One 60-minute test of your technical skills
3. Onsite interviews: A take-home project along with three onsite interviews, which test your technical, LLM, and behavioral fitness for the role

The screening stages will be handled remotely, but you will be expected to complete the final rounds onsite at one of their offices.

Recruiter screen (30 minutes)

Whether you applied online or were referred, your first step will be a very high-level discussion with a recruiter about the company and role. Apart from a few questions about your background, the discussion will mainly focus on Sierra and its goals as a company.

Important details will be shared, including the salary range for agent engineers and an estimate of where you would land based on your experience.

Another detail is your familiarity with specific coding languages, which will come into play in subsequent interviews.

Recruiter Screen Questions:

Technical screen (60 minutes)

You will be given lots of flexibility when scheduling this screen, and some have reported setting it as much as a month out from the recruiter screen. The questions will not be practically related to AI agents, but rather general technical skill assessments.

You will be asked a single question, and the interviewers typically do not add new elements or complexity to the task. You should be prepared to talk through your solution, but the interviewers will not necessarily expect you to “narrate” as you work, so you can explain later.

Common questions include graph traversal/graph search, tree traversal, and other data-structure questions. You might be asked to traverse a linked spreadsheet and search for any cycles or circular references, for example.

Technical Screen Questions:

Onsite round

Apart from the take-home project, each round will be 60 minutes and will be conducted either by other agent engineers on the team or, in the behavioral round, with the hiring manager.

Take-home project

This project will be an assessment not just of your technical skills but also your product sense and your ability to understand customer and user needs. You will be asked to make an AI agent for a fictional client and create the features you think make the most sense.

For example, you might be asked to make an agent for a high-end audio equipment company. You’ll need to train the agent for this use case and choose features from a list that you think suit the company’s needs.

To help you with this work, you’ll be given an OpenAI key to make calls to their API. You’ll also be given a set of questions about observability, performance metrics, and other aspects of the project. You’ll be presenting your work in a later round.

Take Home Project Questions:

Debugging (60 minutes)

Although you technically are not required to understand React.js or Typescript to apply for this role, the debugging round is focused on React and Typescript, and requires you to be able to debug several parts of a React app.

You won’t have access to any AI coding tools or other resources during this challenge, so if you do not have deep familiarity with this branch of JavaScript, you will need to prepare and hone your skills.

This might seem somewhat unusual for this role, but as a startup, Sierra’s team members will sometimes be asked to step outside of their expected responsibilities and assist with front-end work as needed.

Debugging Questions:

Presentation (60 minutes)

This round is broken into two parts of roughly equal size. The first is a presentation of your AI agent, and the second is a discussion of a technical topic of your choice.

You will be asked to send the AI agent project and answers to their questions a few days before this interview. They will have tested and explored your code, and you will be asked a set of high-level questions about your decisions and why you chose certain features.

The second half is meant to test your ability to explain complex technical projects in simple, comprehensible terms. You will have been told about this presentation before and have had a chance to prepare.

You don’t technically need to cover an AI or LLM topic. Still, you should be focused on something you feel not just knowledgeable about but which you can explain in an accessible way to a nontechnical audience.

This is another crucial part of an Agent Engineer’s work at Sierra, as it involves working with customers post-implementation to help them get the most out of their agent.

Presentation Example Questions:

Behavioral (60 minutes)

The hiring manager will conduct this interview and will focus in equal measure on your past experience and the steps you have taken, as well as your approach to cross-functional work, collaboration, and conflict resolution.

Because this role touches on so many different sorts of tasks and also includes direct customer interactions, the manager will want to know that you’ve had a chance to do this kind of work before.

Reviewing your work history, with particular attention to customer interactions, cross-team collaboration, and successful project examples, will help you demonstrate your value to the interviewer. You’ll be repeatedly prompted to give examples, so deep preparation is essential.

Behavioral Questions:

Common Mistakes

Here are some of the mistakes that even experienced agent engineers make when interviewing at Sierra:

• Not having any knowledge of React.js and Typescript
• Not having experience or examples of times when you successfully executed on customer and user feedback
• Not having a good product sense or the ability to understand the unique use cases of different customers
• Not having the autonomy and skills to execute on a take-home assessment successfully
• Expecting your interviewers to understand and follow all of your technical decisions and trade-offs without explaining in detail
• Failing to explain the technical intricacies of agentic AI in a way that customers can understand
• Lacking the flexibility and autonomy to react to changes in organizational priorities and goals

Interview Prep

Understand your role: As a hybrid role that depends on successful communication with customers, you’ll need to prepare in ways that go beyond technical skills. Being a clear communicator, understanding customer issues, and matching solutions to their unique needs are all crucial.

Match their energy: Sierra is known for a warm, passionate, and friendly culture, and you must be able to mirror this back to them, not just to fit in but also because this role is customer-facing. Their culture emphasizes ‘trust’ as a key value, and you’ll want to earn it through consistently positive, productive interactions with team members.

Ask questions and push for clarity: Sierra’s interview process is pretty streamlined compared to other startups, but that doesn’t mean there isn’t potential for chaos or miscommunication. Making sure you understand the details of each project, the languages you are expected to know, and exactly what they want from you in each interview can help reduce the risk of any issues.

About the Role

What are the key characteristics of an Agent Engineer role at Sierra?

• Ownership: Agent engineers are involved in every aspect of the AI agent lifecycle, from development and deployment to post-deployment updates and feedback collection. This makes them a critical part of the present and future of AI agents, as they help decide where the technology should go next.
• Communication: As one of the people most familiar with customer needs and issues, Sierra’s agent engineers are adept at communicating both externally and internally, as this helps the team build better features and proactively address any problems.
• Flexibility: Like at any startup, people are frequently asked to do work outside of their normal routine and comfort zone. Agent engineers are no exception, working cross-functionally with different stakeholders at Sierra to improve their agents.

Core Responsibilities

In addition to their technical and customer interface work, agent engineers might sometimes be called upon to help build frontend UX features, provide subject-matter expertise for marketing efforts, and work through infrastructural limitations. Generally, they’ll be asked to:

• Build, deploy, monitor, and improve AI agents, informed by both their own observability and metrics and customer feedback.
• Help train and specialize AI agents to perform in particular use cases relevant to each business customer.
• Identify and solve persistent performance and reliability issues, and recommend long-term fixes and features to common problems.
• Work cross-functionally across many project types and be able to roll with any changes to organizational priorities.

Compensation

Sierra is known for offering industry-leading salaries across many roles, thanks to its significant fundraising efforts.

Job Requirements

Experience

Although they do not specify a set number of years, comparable roles at Sierra require 5-7 years of relevant experience. For this role, that means working on both scaling systems and communicating with stakeholders about technical topics.

AI/LLM experience is not required but helpful to have, and although there are no coding language requirements, they do require a high degree of competence with React.js and Typescript.

Education

Although there is no degree listed as a requirement for agent engineer roles, other SWE roles at Sierra do require a CS degree or equivalent experience, so it would be beneficial to have. Some subject-matter experts have also noted that MBAs with technical skills are highly prized at Sierra.

Resources

• Sierra Careers Page
• Sierra About Page
• Sierra Blog
• Software Engineering Interview Prep
• Generative AI Interview Prep
• Software Engineer Interview Questions

FAQs

How long is the Sierra Agent Engineer interview process?

Like most startups, there is a great deal of flexibility, especially during rapid growth phases, and you will be given a lot of scheduling flexibility for each round. Most report the process taking between two and five weeks.

Do I need AI experience to apply at Sierra?

AI experience is not technically expected for this role, but it is crucial that you have a thorough understanding of AI agents and how they are typically used. You’ll need to build an agent as part of the interview process, so some experience will be critical.

Does Sierra have internships?

Sierra offers internships and early-career roles through its Early Career Program, which is primarily geared towards recent grads but also offers roles for students.

Does Sierra allow remote work?

Sierra is an on-site company, but they do have some flexibility for occasional remote work. They have offices in San Francisco, Atlanta, London, and New York.