Gtm AI Engineer

Pendo Pendo · Enterprise · Raleigh, NC · Data & GTM Intelligence

Applied AI Engineer role focused on building and deploying AI-powered solutions for Go-To-Market (GTM) teams at Pendo. The role involves owning the full lifecycle of AI solutions, from problem definition and prompt design to production deployment and iteration, with a strong emphasis on practical application and business outcomes. The ideal candidate is a builder with engineering skills and a deep understanding of when and how to apply AI effectively.

What you'd actually do

  1. Own AI solutions end-to-end: problem definition, prompt design, production deployment, monitoring, and iteration — you ship, you watch, you improve.
  2. Build and manage GTM workflow automations that reduce manual work across Sales, Marketing, and Customer Engineering systems, including Slackbots and other integrations.
  3. Partner directly with GTM stakeholders to surface high-value problems, validate solutions, drive adoption, and set honest expectations about AI capabilities and limitations.
  4. Develop and maintain prompt management practices that make AI outputs reliable, auditable, and improvable over time — treat prompts as production code, not experiments.
  5. Work with the Data Platform and Systems teams to identify foundational tooling gaps and contribute clear, actionable requirements based on what you encounter in production.

Skills

Required

  • software engineering
  • solutions engineering
  • applied AI
  • LLM-powered applications
  • prompt engineering
  • output validation
  • iterative improvement
  • stakeholder management
  • problem definition
  • production deployment
  • monitoring
  • iteration

Nice to have

  • GTM systems and workflows
  • Salesforce experience
  • Slackbots
  • workflow automations
  • shared prompt library
  • AI pattern documentation
  • quantifying business impact of AI solutions
  • efficiency or revenue metrics

What the JD emphasized

  • strong track record of shipping production systems
  • Hands-on experience building LLM-powered applications
  • prompt engineering
  • output validation
  • iterative improvement in a live environment
  • Strong judgment about when AI is the right tool
  • willingness to push back clearly when it isn't
  • Ability to work directly with non-technical business stakeholders
  • drive adoption without hand-holding
  • A builder's posture

Other signals

  • shipping AI-powered solutions
  • production deployment
  • iterative improvement
  • GTM stakeholders
  • AI as a tool