GTM Engineer

Endor Labs

About The Position

As an AI GTM Engineer, you will drive Endor Labs’ internal AI transformation. In close coordination with the CEO and E-Staff, you will work across non-engineering functions—including Sales, Marketing, Business Development, BizOps, and G&A—to identify high-impact opportunities for AI agents and automation to improve productivity, speed, and quality. This is a hands-on role involving the development and deployment of AI-powered workflows, from proof of concept through production. You will work with department heads to understand workflows, pain points, and operational bottlenecks, then design, build, and deploy AI agent-based solutions using platforms such as Claude and Gemini, along with custom integrations. Solutions may automate repetitive work, enhance decision-making, and increase organizational capacity. You will also lead change management by training teams, developing internal champions, measuring adoption, and iterating until AI is integrated into everyday work.

Requirements

5+ years of experience in a combination of software engineering, data science, AI/ML engineering, or technical operations.
Proven ability to build and ship AI-powered solutions in a business context, including production systems used by teams daily.
Deep understanding of go-to-market operations, including Sales, Marketing, Business Development, and BizOps workflows.
Understanding of enterprise sales cycles and pipeline mechanics, and ability to identify high-leverage AI opportunities.
Strong change management instincts, including the ability to drive adoption, build trust, and shift behaviors.
A builder mindset suited to startup environments, comfort with ambiguity, and a preference for shipping and iterating.

Responsibilities

Assess workflows across functions to identify opportunities for automation and AI augmentation.
Build and maintain an AI opportunity roadmap, prioritizing use cases by ROI, feasibility, and strategic value in partnership with department heads and the CEO.
Evaluate new AI models, platforms, tools, and agent frameworks.
Design, build, and deploy AI agent-based workflows and automations, including multi-step agentic workflows, RAG-based knowledge systems, automated content pipelines, and intelligent CRM enrichment.
Own the lifecycle of AI solutions from rapid prototyping through production deployment, including monitoring, error handling, and iteration based on user feedback.
Integrate AI solutions with existing systems such as Salesforce, HubSpot, Slack, Google Workspace, and internal databases.
Design and execute a change management strategy to drive AI adoption across the organization.
Develop and deliver department-specific training programs, workshops, and hands-on enablement sessions.
Identify and cultivate AI champions within teams.
Track adoption metrics, gather feedback, and iterate on tools and training.