GTM AI Engineer -Deal Desk
Motive · United States · 1 mo ago
RemoteRemoteEngineering$140k–$160k/yrFull-time
We need to output HTML fragment with sections: headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We need to parse the job posting.
We have sections: Who We Are (company description) - not a required heading; we can maybe include as About the role? Actually "About The Role" is a heading. We'll treat that as About the role.
We need to extract content for each section.
Let's parse:
Who We Are: description of Motive.
About The Role: description of GTM Engineer on Deal Desk team, responsibilities etc.
What You'll Do: list of duties.
What We're Looking For: qualifications/requirements.
Pay Transparency: includes compensation range and benefits.
We also have benefits described: health, pharmacy, optical and dental care benefits, paid time off, sick time off, short term and long term disability coverage, life insurance as well as 401k contribution.
Pay: compensation range: United States $140,000—$160,000 USD.
Schedule: not mentioned.
Thus we will have sections: About the role, Responsibilities (What You'll Do), Requirements (What We're Looking For), Benefits, Pay.
We might also include Qualifications? Could combine Requirements and Qualifications. But we need to follow instruction: use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We can choose which to include based on content.
We have content for About the role, Responsibilities, Requirements (maybe Qualifications), Benefits, Pay.
We could also include Skills if we extract from requirements. But we can keep Requirements as a combined section.
We must not repeat job title as heading. Not include Job ID etc.
We must remove boilerplate: EEO, equal-opportunity, scam-warning, privacy notices, export regulations, etc. Also remove navigation, cookie, legal.
We must preserve all substantive information.
We need to output only HTML fragment, no /, no markdown fences.
Thus produce something like:
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It doesn't forbid other headings, but we should follow those examples. The Who We Are is not in list; maybe we can omit or incorporate into About the role? The About the role section already has description of role; we could prepend company overview as a paragraph before responsibilities. That would preserve info.
Thus About the role content: combine Who We Are paragraph + About The Role paragraph.
Let's capture Who We Are text:
"Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks. Motive serves nearly 100,000 customers – from Fortune 500 enterprises to small businesses – across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector. Visit gomotive.com to learn more."
About The Role paragraph:
"As a GTM Engineer on the Deal Desk team, you’ll 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’ll 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."
We'll combine these two paragraphs into About the role section.
Now Responsibilities: What You'll Do bullet points.
Let's extract each bullet:
- 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
We need to preserve all.
Now Requirements: What We're Looking For bullet points.
Extract:
- 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.
We could also include "Pay Transparency" section for Pay and Benefits.
Pay: "The compensation range for this position will depend on where you reside. For this role, the compensation range is: United States $140,000—$160,000 USD"
Also mention: "Your compensation may be based on several factors, including education, work experience, and certifications. For certain roles, total compensation may include restricted stock units."
We should include that as part of Pay section.
Benefits: "Motive offers benefits including health, pharmacy, optical and dental care benefits, paid time off, sick time off, short term and long term disability coverage, life insurance as well as 401k contribution (all benefits are subject to eligibility requirements). Learn more about our benefits by visiting Motive Perks & Benefits."
We'll include that.
We must not include boilerplate like "Creating a diverse and inclusive workplace is one of Motive's core values. We are an equal opportunity employer..." etc. Also remove privacy notices, export regulations, etc.
Now construct HTML.
We'll have:
for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We need to parse the job posting.
We have sections: Who We Are (company description) - not a required heading; we can maybe include as About the role? Actually "About The Role" is a heading. We'll treat that as About the role.
We need to extract content for each section.
Let's parse:
Who We Are: description of Motive.
About The Role: description of GTM Engineer on Deal Desk team, responsibilities etc.
What You'll Do: list of duties.
What We're Looking For: qualifications/requirements.
Pay Transparency: includes compensation range and benefits.
We also have benefits described: health, pharmacy, optical and dental care benefits, paid time off, sick time off, short term and long term disability coverage, life insurance as well as 401k contribution.
Pay: compensation range: United States $140,000—$160,000 USD.
Schedule: not mentioned.
Thus we will have sections: About the role, Responsibilities (What You'll Do), Requirements (What We're Looking For), Benefits, Pay.
We might also include Qualifications? Could combine Requirements and Qualifications. But we need to follow instruction: use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We can choose which to include based on content.
We have content for About the role, Responsibilities, Requirements (maybe Qualifications), Benefits, Pay.
We could also include Skills if we extract from requirements. But we can keep Requirements as a combined section.
We must not repeat job title as heading. Not include Job ID etc.
We must remove boilerplate: EEO, equal-opportunity, scam-warning, privacy notices, export regulations, etc. Also remove navigation, cookie, legal.
We must preserve all substantive information.
We need to output only HTML fragment, no /, no markdown fences.
Thus produce something like:
About the role
...
Responsibilities
- ... ...
Requirements
- ... ...
Benefits
- ... ...
Pay
...
We need to ensure we preserve all substantive info from sections. Let's extract. Who We Are: Not needed as a heading? Could be part of About the role? But we have separate About the role section. The Who We Are is company overview; could be included in About the role? Probably not needed; but we could include as part of About the role? The instruction: "use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It doesn't forbid other headings, but we should follow those examples. The Who We Are is not in list; maybe we can omit or incorporate into About the role? The About the role section already has description of role; we could prepend company overview as a paragraph before responsibilities. That would preserve info.
Thus About the role content: combine Who We Are paragraph + About The Role paragraph.
Let's capture Who We Are text:
"Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks. Motive serves nearly 100,000 customers – from Fortune 500 enterprises to small businesses – across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector. Visit gomotive.com to learn more."
About The Role paragraph:
"As a GTM Engineer on the Deal Desk team, you’ll 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’ll 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."
We'll combine these two paragraphs into About the role section.
Now Responsibilities: What You'll Do bullet points.
Let's extract each bullet:
- 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
We need to preserve all.
Now Requirements: What We're Looking For bullet points.
Extract:
- 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.
We could also include "Pay Transparency" section for Pay and Benefits.
Pay: "The compensation range for this position will depend on where you reside. For this role, the compensation range is: United States $140,000—$160,000 USD"
Also mention: "Your compensation may be based on several factors, including education, work experience, and certifications. For certain roles, total compensation may include restricted stock units."
We should include that as part of Pay section.
Benefits: "Motive offers benefits including health, pharmacy, optical and dental care benefits, paid time off, sick time off, short term and long term disability coverage, life insurance as well as 401k contribution (all benefits are subject to eligibility requirements). Learn more about our benefits by visiting Motive Perks & Benefits."
We'll include that.
We must not include boilerplate like "Creating a diverse and inclusive workplace is one of Motive's core values. We are an equal opportunity employer..." etc. Also remove privacy notices, export regulations, etc.
Now construct HTML.
We'll have:
About the role
Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks. Motive serves nearly 100,000 customers – from Fortune 500 enterprises to small businesses – across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector. Visit gomotive.com to learn more. As a GTM Engineer on the Deal Desk team, you’ll 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’ll 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.
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