Level

Sierra

GTM Engineer

Sierra is hiring a GTM Engineer in San Francisco, United States. It pays $150k-$230k a year and Level rates it ; you can apply on Sierra.

Level's read on this job

  • Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Tools and skills the posting cites include OpenAI, Clay and prompt engineering.
  • Level lists 209 other open roles at Sierra.

AI in this role

openaiclay
prompt-engineeringai-agents

About us

Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia.

We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do.

Our co-founders are Bret Taylor and Clay Bavor. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace.

What you'll do

  • Implement Go-to-Market software for our marketing, sales, and agent development teams

  • Design and build the automated workflows, integrations, and AI-powered systems that turn signal into pipeline, across enrichment, scoring, routing, and outbound activation

  • Own our enrichment infrastructure end-to-end: the pipelines that take a new signup, demo request, or event attendee list and return a fully enriched, scored, Salesforce-upserted record across Clay, ZoomInfo, Cognism, and LLM-powered sources

  • Build AI agents and AI-powered internal tools that compound sales team output — account research, call summarization, RFP and security questionnaire response, proposal generation, and Slack-accessible agents that surface account intel on demand

  • Build and improve the fit scoring pipeline that evaluates every account against our ICP and writes results to Postgres and Salesforce, including signal design, batching, retry logic, and continuous improvement of the underlying models

  • Develop data architecture using Postgres, Fivetran pipelines, and reverse ETL. Keep data jobs healthy and in sync with the tools that consume them; track downstream impact when schemas and apps change

  • Ship production code with PR review, observability, and proper error handling and debug production incidents (Salesforce platform failures, enrichment failures, LLM timeouts)

What you'll bring

  • 3+ years in GTM Engineering, Revenue Operations, Sales Engineering, Growth Engineering, or a closely adjacent technical role at a high-growth B2B SaaS company

  • Python and TypeScript skills: You write clean code, understand async patterns, can design a database schema, and can debug a production incident from logs alone

  • Hands-on experience inside a modern GTM stack (Salesforce, HubSpot, Outreach, Clay, enrichment providers): You understand how leads flow through a CRM and why data quality degrades over time

  • Production experience with LLMs: Prompt design, eval loops, error handling, and the difference between a demo and a system you can trust at scale

  • Strong working knowledge of SQL, schemas, and data flow across GTM and warehouse systems

  • Systems thinking: You’ve built data pipelines and think about what happens at 10x volume, when an API goes down, or when the same account hits your queue five times in parallel

  • Owner's mindset: You take accountability from code to deployment to adoption, define scope with minimal direction, and ship good solutions over perfect ones

Even better…

  • Built applications using LLMs, ideally with exposure to production-grade AI/ML systems

  • Developed custom Salesforce solutions using apex classes, apex triggers, LWC, SLDS

  • Integrated salesforce with other business systems using REST/SOAP APIs, Platform Events, and External Services

Our values

  • Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work.

  • Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it.

  • Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve.

  • Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time.

  • Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements.

What we offer

We want our benefits to reflect our values and offer the following to full-time employees:

  • Flexible (unlimited) paid time off

  • Medical, dental, and vision benefits for you and your family

  • Life insurance and disability benefits

  • Retirement plan dependent on country of employment

  • Parental leave

  • Fertility and family building benefits through Carrot

  • Lunch, as well as delicious snacks and coffee to keep you energized 

  • Discretionary benefit stipend giving people the ability to spend where it matters most

  • Free alphorn lessons

These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies.

Be you, with us

We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

How we rate this

GTM Engineer at Sierra rates 66 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

Prompt engineeringAI agentsOpenAIClay

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. What are the limits of OpenAI that you've run into, and how did you work around them?
  4. What's a project where you used Clay hands-on?
  5. Describe a typical day in a role like this one: which parts run through AI directly?

Adapt your resume

  • List these exact terms on your resume: Prompt engineering, AI agents, OpenAI, and Clay. 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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