GTM AI Engineer -Deal Desk

Motive

19d•$140,000 - $160,000•Remote

About The Position

As a GTM Engineer on the Deal Desk team, you will build and own practical AI-powered workflows, automations, and agents that improve how our Sales and GTM teams operate. You will be an operational Builder, continually scanning Deal Desk workflows for AI-solvable problems, turning team and stakeholder challenges into scalable, repeatable tools. You will partner with Deal Desk, Product, ESYS, and business stakeholders to identify high-value use cases, prototype solutions, launch secure production tools, and measure adoption and business impact for teams ranging from SMB to Strategic. You will own the full development lifecycle for internal Deal Desk AI tools, from initial prototyping and proof-of-concept development through production scaling, beta testing with end users, ongoing maintenance, and continuous improvement. The ideal candidate has practical business experience on a GTM or RevOps team. We're looking for someone with an experimentation mindset—eager to prototype, learn quickly from failure, and explore new ideas. You should be passionate about AI’s potential to transform work and have a strong grasp of concepts like context windows, token usage, compute costs, chunking, and performance benchmarks. Experience with scripting, SQL/SOQL, Python basics, and prompt engineering using models like ChatGPT, Gemini, Claude, etc., via web and API is essential. Familiarity with the evolving agentic ecosystem, and the ability to explain technical topics to non-technical audiences, especially in a GTM context, is key.

Requirements

5-7 years of hands-on Deal Desk or RevOps experience, including solving business challenges with tooling, building and deploying internal tools, automations, data products, or AI-enabled workflows in an enterprise environment. Relevant backgrounds may include AI/ML engineering, Salesforce or business systems, data, software development, or workflow automation.
Hands-on experience with CPQ and CLM platforms
Strong understanding of AI fundamentals such as context windows, token consumption, compute cost, chunking, and performance benchmarks
Understanding of API usage, limitations, and how to leverage API’s to aggregate data across multiple source platforms. This includes an understanding of rate limits scalable API use as it pertains to both data sources and LLM’s
Understanding of scripting, SQL / SOQL, and Python fundamentals
Experience leveraging foundational models (Gemini, ChatGPT, Perplexity, Claude, Grok and others), both through the web interface and via the API
Familiarity with the rapidly evolving agentic landscape, including orchestration layers, MCP, Agent2Agent, and Salesforce-native agent platforms such as Agentforce and ClaudeForce. Experience building agents, workflows, or React-based user interfaces directly within Salesforce is preferred.

Nice To Haves

Practical business experience on a GTM or RevOps team.
Experimentation mindset—eager to prototype, learn quickly from failure, and explore new ideas.
Passionate about AI’s potential to transform work.
Ability to explain technical topics to non-technical audiences, especially in a GTM context.
Experience building agents, workflows, or React-based user interfaces directly within Salesforce is preferred.

Responsibilities

Operate with the default question: “How can I use AI to solve this?”, consistently identifying Deal Desk bottlenecks to automate in order to provide the best possible experience for our stakeholders.
Design robust human-in-the-loop validation, audit trails, and fallback rules for Deal Desk agents to ensure complete compliance with revenue recognition policies and pricing approval matrices.
Own the full development cycle of prototyping / developing proof of concepts, scaling prototypes for production use, beta testing with end users, and performing ongoing maintenance for internal AI tools that support our GTM/Deal Desk and Sales partners. This includes building agents and workflows using Glean, Salesforce—including Agentforce and ClaudeForce—and n8n; developing front-end applications using Retool, Cursor, React, or similar tools; integrating enterprise data and APIs securely; and creating prompts and workflows for models such as Gemini, ChatGPT, Claude, and Perplexity.
Ensure agents and applications follow UX best practices and can be easily leveraged by a less technical business audience
Manage a cost envelope for production use cases, testing different LLM models to balance performance with token consumption cost
Create and maintain documentation around launched solutions
Train end-users on the usage of launched tools