S

Sierra

Builds AI agents for customer conversations

GTM Engineer

AI Application Engineering +1Updated on Nov 11
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • At least 3 years of experience in GTM Engineering, Revenue Operations, Sales Engineering, Growth Engineering, or a closely adjacent technical role at a high-growth B2B SaaS company.
  • Proficiency in Python and TypeScript, including writing clean code, understanding asynchronous patterns, designing database schemas, and debugging production incidents from logs.
  • Hands-on experience with a modern go-to-market stack, including Salesforce, HubSpot, Outreach, Clay, and enrichment providers, and understanding of lead flow through a CRM and how data quality degrades.
  • Production experience with large language models, including prompt design, evaluation loops, error handling, and building reliable systems at scale.
  • Strong working knowledge of SQL, schemas, and data flow across go-to-market and warehouse systems.
  • Experience building data pipelines and considering system behavior at higher volumes, during API outages, and when duplicate accounts enter a queue in parallel.
  • Ability to take accountability from code through deployment and adoption, define scope with minimal direction, and deliver solutions.

Responsibilities

  • Implement go-to-market software for marketing, sales, and agent development teams.
  • Design and build automated workflows, integrations, and AI-powered systems for signal-to-pipeline processes, including enrichment, scoring, routing, and outbound activation.
  • Own enrichment infrastructure end-to-end, including pipelines that enrich, score, and upsert signup, demo request, or event attendee records to Salesforce using Clay, ZoomInfo, Cognism, and large-language-model-powered sources.
  • Build AI agents and AI-powered internal tools for account research, call summarization, RFP and security questionnaire responses, proposal generation, and Slack-accessible account intelligence.
  • Build and improve the fit-scoring pipeline that evaluates accounts against the ideal customer profile and writes results to Postgres and Salesforce, including signal design, batching, retry logic, and continuous model improvement.
  • Develop data architecture using Postgres, Fivetran pipelines, and reverse ETL; keep data jobs healthy and synchronized with consuming tools, and track downstream impacts of schema and application changes.
  • Ship production code with pull-request review, observability, and appropriate error handling, and debug production incidents involving Salesforce platform failures, enrichment failures, and LLM timeouts.

Desired Qualifications

  • Build applications using large language models, ideally with exposure to production-grade AI/ML systems.
  • Develop custom Salesforce solutions using Apex classes, Apex triggers, Lightning Web Components, and Salesforce Lightning Design System.
  • Integrate Salesforce with other business systems using REST/SOAP APIs, Platform Events, and External Services.

About the Company

Sierra

Builds AI agents for customer conversations

Sierra builds AI agents that handle customer conversations for businesses, from answering support questions to guiding purchases and managing account requests. Companies deploy the same agent across voice, chat, email, and messaging channels, with behavior shaped by their brand guidelines and business policies. Its Ghostwriter tool creates and updates agents from plain instructions or existing company materials, then tests changes before teams approve them. The platform connects agents to business systems so they take action, and Sierra charges for completed outcomes rather than the AI tokens consumed. Sierra was founded in 2023 and is headquartered in San Francisco, California, United States.

Company size
1,001-5,000
Company stage
Series E
Total funding
$1.6B
Headquarters
San Francisco, CA
Founded
2023

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