GTM Engineer (Deal Desk) - AI-Powered Workflow Automation

What You’ll Do:

• 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 (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.

What We’re Looking For:

• 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 APIs to aggregate data across multiple source platforms. This includes an understanding of rate limits and 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.