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Perplexity AI

Builds AI search and research tools

Growth GTM Engineer - Revenue Operations

Sales OperationsPosted on Nov 13
Full-time$175k - $235k /yrHybrid

About the Job

Requirements

  • At least 4 years of experience in GTM engineering, Revenue Operations, Marketing Operations engineering, growth engineering, or data engineering in a B2B SaaS environment, including at least 2 years building enrichment, scoring, or routing systems.
  • Ability to begin with a revenue problem and determine the data, logic, or tool needed to solve it.
  • Strong SQL skills and experience building data models in a data warehouse such as Snowflake or dbt; able to query data independently.
  • Production coding experience in Python or TypeScript, including shipping internal tools, integrations, or agents relied on by users.
  • Deep working knowledge of the Salesforce data model, including leads, contacts, accounts, opportunities, campaigns, and ownership, and experience automating within and integrating with Salesforce.
  • Hands-on experience with enrichment and intent providers and orchestration tools such as Clay, ZoomInfo, Apollo, Clearbit, 6sense, Demandbase, or Common Room.
  • Knowledge of lead lifecycle design, scoring models, routing and assignment logic, service-level agreements, attribution data, and conversion metrics.
  • Comfort working with REST APIs, webhooks, OAuth, rate limits, and error handling across third-party go-to-market tools.
  • Ability to work directly with sales representatives and marketers and deliver fixes without requiring a product manager to translate requests.

Responsibilities

  • Design and operate waterfall enrichment across third-party data providers, AI research agents, and first-party data for marketing and product leads; manage lead-to-account matching, deduplication, field governance, data freshness, and provider costs so records are accurate and actionable.
  • Build and iterate on lead and account scoring using firmographic and technographic attributes, intent, engagement, event activity, and product usage signals; calibrate models against closed-won and closed-lost data, version them, and explain scores to Sales.
  • Design lead-routing decision logic based on score, segment, territory, account ownership, capacity, and existing opportunities; co-define lifecycle stages, handoff service-level agreements, recycle rules, and speed-to-lead triggers, and enforce them in Salesforce and routing tools.
  • Instrument the funnel from lead creation through MQL, meeting, opportunity, and closed-won; identify lead drop-off and predictive sources and signals, validate qualification criteria, feed insights into scoring, routing, and Marketing programs, and supply attribution data.
  • Build prospect-engagement tools for representatives, including research briefs, Slack and Salesforce alerts, prioritized outreach queues, and LLM-powered outreach and preparation agents; gather user feedback, track adoption, retire unused tools, and integrate vendor tools with Salesforce and the data layer.
  • Build and maintain dbt models, reverse ETL syncs, APIs, and webhooks connecting Snowflake, Salesforce, marketing automation, enrichment providers, and engagement tools; ensure data flows are observable, tested, and trusted, and support the rollout of the first marketing automation platform by building Salesforce and warehouse syncs.
  • Partner with Marketing, Growth, BDR and Sales leadership, Data Science, and Sales Systems to turn processes into durable systems; use Growth team's published product-led growth signals to improve scoring and routing.
  • Audit enrichment coverage, scoring logic, routing rules, and lead service-level agreements, and document gaps that cost pipeline.
  • Ship an enrichment waterfall with measurable gains in fill rate and accuracy.
  • Ship an improved unified scoring model combining fit, intent, and product signals, with a published rubric trusted by Sales.
  • Ship routing that sends every lead to nurture or sales within an agreed service-level agreement, with dashboards showing speed to lead and conversion by route.
  • Ship at least one representative-facing engagement app or agent with sustained weekly use by BDRs and AEs within the first six months.
  • Demonstrate measurable lift in MQL-to-meeting and meeting-to-opportunity conversion.

Desired Qualifications

  • Experience in a hybrid product-led growth and sales-led motion, including product-qualified leads, mapping users to accounts, and sales-assist routing.
  • Experience with routing and scheduling tools such as Default, Chili Piper, or LeanData, and reverse ETL tools such as Hightouch, Census, or Polytomic.
  • Experience building LLM-powered research, personalization, or qualification agents, including evaluation and monitoring.
  • Experience with statistical or machine-learning-based scoring, such as logistic regression or gradient boosting, and model calibration.
  • Experience with entity resolution and domain matching at scale.
  • Prior GTM Engineer experience at a go-to-market tooling or AI-native company.

About the Company

Perplexity AI

Builds AI search and research tools

Perplexity AI builds AI search and research tools for individuals and organizations, combining web retrieval with written answers that link to their sources. Users ask questions in its website or apps, upload files for analysis, and follow up in a conversation, while its Comet browser brings an AI assistant into everyday browsing. Enterprise accounts connect internal files and applications with web research, and developers use its search and agent APIs to add these capabilities to their own software. The company earns money from paid personal and business subscriptions and usage charges for its APIs, alongside free consumer access. Perplexity AI was founded in 2022 and is headquartered in San Francisco, California.

Company size
201-500
Company stage
Private
Total funding
$1.7B
Headquarters
San Francisco, CA
Founded
2022

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