Generative AI Sales Engineer (Unpaid Internship)

Generative AI Sales Engineer (Unpaid Internship / Training)

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Remote | Dallas, Texas, United States

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Work authorization: Applicants must be authorized to work in the United States for this role. F-1 CPT or OPT candidates may apply where their authorization permits this specific role.

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Role Overview

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The Generative AI Sales Engineer is a hybrid engineering and commercial role responsible for strengthening the technical capabilities of the sales process. This role combines engineering thinking, Generative AI, proposal development, and client engagement to help the company identify, develop, and convert business opportunities.

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The ideal candidate is technically capable, commercially aware, comfortable working with AI tools, and able to translate client needs into clear and compelling technical proposals.

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Compensation Structure

This position begins with an unpaid internship and training period, during which there is no guaranteed base salary.

Participants are eligible for performance-based closing bonuses calculated as a percentage of realized free cash flow attributable to each approved closed deal.

The bonus rate begins at 5% for the first closing and increases by 1 percentage point for each subsequent closing, up to a maximum of 10% per closing.

Bonus payments are subject to company verification and confirmation of the applicable realized free cash flow.

High-performing participants may be considered for transition to a paid, salaried position based on demonstrated performance, successful completion of the initial period, and business needs; however, such transition is not guaranteed.

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Key Responsibilities

Improve Sales Tools Using Engineering Frameworks

• Design and continuously improve tools, templates, and workflows that make the sales process more systematic and efficient.
• Apply engineering frameworks and structured problem-solving methods to opportunity qualification, solution design, estimation, and proposal development.
• Develop reusable technical frameworks, calculators, checklists, and decision-support tools for the sales team.
• Identify opportunities to automate repetitive sales and proposal activities.
• Collaborate with sales and engineering teams to improve the accuracy and quality of technical information used throughout the sales process.

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Develop Proposals Using Generative AI

• Prepare high-quality technical and commercial proposals based on client requirements.
• Use Generative AI tools to accelerate proposal research, drafting, customization, review, and quality assurance.
• Translate technical solutions into clear business value for prospective clients.
• Develop and maintain reusable proposal templates, knowledge bases, prompts, and supporting content.
• Verify AI-generated content for technical accuracy, consistency, relevance, and professionalism.
• Continuously improve the company's AI-assisted proposal development workflow.

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Maintain Prospective Client Relationships

• Build and maintain professional relationships with prospective clients throughout the sales cycle.
• Participate in discovery calls, technical discussions, presentations, and follow-up meetings.
• Understand client requirements, business challenges, technical constraints, and decision criteria.
• Coordinate with internal technical and commercial teams to provide timely responses to client questions.
• Maintain consistent follow-up with prospective clients and help ensure opportunities continue progressing through the pipeline.
• Help establish the company as a credible technical partner throughout the pre-sales process.

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Maintain and Review Sales KPIs

• Regularly maintain sales pipeline and performance data.
• Monitor key sales metrics, including proposal volume, pipeline value, conversion rates, proposal turnaround time, win/loss rates, and opportunity progression.
• Conduct periodic reviews to identify bottlenecks and opportunities for improvement.
• Ensure sales information and dashboards remain accurate and up to date.
• Translate KPI findings into practical recommendations for improving sales performance.
• Support management with regular sales performance reporting and analysis.

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Required Skills & Competencies

• Strong engineering and structured problem-solving mindset.
• Excellent technical and business writing skills.
• Practical experience with Generative AI and AI-assisted productivity tools.
• Ability to understand technical requirements and translate them into commercial proposals.
• Strong communication, presentation, and client relationship skills.
• Analytical mindset with confidence working with KPIs and business data.
• Ability to coordinate effectively across engineering, sales, and management teams.
• Strong attention to detail and ability to manage multiple proposals and opportunities simultaneously.
• Proficiency with spreadsheets, presentation tools, CRM systems, and related sales technologies.

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Preferred Qualifications

• Bachelor's degree in Engineering, Computer Science, Data Science, Business Engineering, or a related field.
• Experience in sales, pre-sales, solution engineering, technical sales, consulting, or business development.
• Experience developing proposals, RFP/RFQ responses, quotations, or technical documentation.
• Familiarity with AI/ML, data science, software, or technology-driven projects.
• Experience using CRM, sales analytics, automation, or proposal management tools.

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Key Performance Indicators

Performance for the Generative AI Sales Engineer may be measured through:

• Proposal turnaround time and quality.
• Proposal-to-opportunity and opportunity-to-win conversion rates.
• Sales pipeline progression and data accuracy.
• Quality and effectiveness of AI-assisted proposal workflows.
• Adoption and effectiveness of newly developed sales tools and frameworks.
• Client engagement and follow-up consistency.
• Accuracy and timeliness of sales KPI reporting.
• Contribution to overall sales pipeline and revenue growth.

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What Success Looks Like

A successful Generative AI Sales Engineer makes the sales organization more technical, systematic, and efficient. They shorten the time required to develop strong proposals, improve the quality of client-facing technical communication, create effective tools and frameworks for the sales team, maintain strong relationships with prospective clients, and use performance data to continuously improve the sales process and contribute to revenue growth.