GTM Engineer

Posted 9 Hours Ago
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London, Greater London, England, GBR
In-Office
Entry level
Big Data • Marketing Tech • Software
The Role
Build and deploy production-grade AI agents, LLM pipelines, integrations, and GTM workflows for sales, customer success, and marketing. Own architecture, prototyping, evaluation, deployment, observability, data quality, and enablement. Integrate Salesforce and GTM tools, transform revenue and customer data into signals, automate workflows, evaluate new technologies, and improve productivity, pipeline acceleration, renewals, expansion, adoption, and data quality.
Summary Generated by Built In
Competencies

You are an applied AI engineer whose product is the revenue engine. You find where the customer lifecycle can work better and ship production-grade agentic workflow, LLM pipelines and integrations that make each process best in class for reps, CSMs and marketers. You operate independently and own each build end to end: architecture, prototype, evals, deployment and observability. You spar on solution design with the team, then ship.

We care more about what you have shipped than where you studied. If you have built something real, show us.

Must-haves

  • You have shipped AI systems GTM teams use daily. Agents, workflows or integrations used by sales, CS or marketing that moved a number.

  • Strong integration skills in JavaScript or TypeScript. You’re comfortable building and running integration services. Working with APIs and webhooks, handling auth, rate limits and errors, and shipping tested code.

  • Hands-on Salesforce or equivalent, declarative and code. Declarative: object model, Flows, validation rules, permission sets, record types. Code: Apex triggers and classes, SOQL and SOSL, Lightning Web Components, Platform Events and Change Data Capture, REST and Bulk APIs, SFDX deployments.

  • Applied AI engineering. You build with LLM APIs, not just chat interfaces, and can show the skills listed below in real work.

  • You understand the revenue engine. Experience in RevOps, GTM Systems, growth or a GTM engineering agency in B2B SaaS. You know how pipeline, renewals and expansion actually work.

  • Data quality fundamentals. SQL, CRM data models, deduplication, enrichment waterfalls and data quality at scale.

  • GTM data stack. Clay, n8n, Make + warehouse and reverse ETL experience.

  • Production mindset. You ship fast and build things others can maintain: logged, monitored, documented.

  • Clear communicator. You can sit with a top rep, find the work that shouldn't exist, and explain the fix in plain words.

Nice-to-haves

  • Experience with a customer platform or CSM tool (Planhat, Gainsight, ChurnZero), or HubSpot alongside Salesforce.

  • Salesforce certifications such as Platform Developer I or II, or Platform App Builder.

  • Side projects, open-source tools, public write-ups or a GitHub that shows you build for fun.

  • Founder, agency or early-stage startup experience.

Trajectory

You’ll own each build end to end, from architecture and prototype through evals, deployment and observability. Here’s what that looks like:

  • Agentic GTM workflows: Design and ship AI agents and workflows that optimise productivity: account research, signal detection, enrichment, call and email analysis, personalised outreach, renewal and expansion plays.

  • Planhat on Planhat: Run our own GTM on our own platform. Build with Planhat's AI, automations and APIs, and feed what you learn straight back to Product as a power user.

  • Signals and data: Turn product usage, intent, firmographic and conversation data into scores and triggers that route the right account to the right person at the right time.

  • Integrations: Connect tools that don't talk natively. Build the webhooks, MCP connection and transformations that keep data clean across the stack.

  • Build vs buy: Run tight pilots on new GTM and AI tools, measure fit and ROI, and make a clear call.

  • Enablement: Document what you build, teach teams to use it with confidence, and raise how the whole company builds with AI.

Definition of Success

Success is measured in outcomes: productivity gains, pipeline acceleration, data quality and adoption of what you ship.

Skills Required

  • Experience shipping AI systems, agents, workflows, or integrations used daily by sales, customer success, or marketing teams
  • Strong JavaScript or TypeScript integration development skills, including APIs, webhooks, authentication, rate limits, error handling, and tested code
  • Hands-on Salesforce experience with declarative configuration and development, including Flows, validation rules, permission sets, record types, Apex, SOQL, SOSL, Lightning Web Components, Platform Events, Change Data Capture, REST APIs, Bulk APIs, and SFDX
  • Applied AI engineering experience building with LLM APIs and production AI systems
  • Experience in RevOps, GTM Systems, growth, or a GTM engineering agency in B2B SaaS
  • Understanding of pipeline, renewals, and expansion processes
  • SQL, CRM data models, deduplication, enrichment waterfalls, and data quality at scale
  • Experience with Clay, n8n, Make, data warehouses, and reverse ETL
  • Production engineering practices including logging, monitoring, documentation, and maintainable systems
  • Clear communication skills with business and revenue teams
  • Experience with Planhat, Gainsight, ChurnZero, or HubSpot
  • Salesforce Platform Developer I or II, or Platform App Builder certification
  • Side projects, open-source tools, public write-ups, or a GitHub portfolio
  • Founder, agency, or early-stage startup experience
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The Company
150 Employees
Year Founded: 2015

What We Do

Planhat is a customer platform built to give insights, manage workflow and drive customer experience. Planhat is helping hundreds of modern technology companies worldwide center their business around their customers in order to maximize customer success and customer lifetime value. The company was founded in Stockholm, Sweden in 2015 and has a team of 100+ people across Europe, North America, South America, and APAC.

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