AI Workflow Intern

Purpose

Functions

• Develop and Refine AI Prompt Systems – Design, test, and optimize prompts across multiple LLM platforms (ChatGPT, Claude, Gemini, etc.) to extract contextual information from the Company OS and generate intelligent, actionable outputs for founders and staff.

• Build Automation Workflows – Implement provided architecture specifications and create new automation workflows from scratch using scheduled events, webhooks, and integration platforms to trigger context-aware AI responses.

• Execute Systematic Testing and Refinement – Follow structured test plans to evaluate automation performance, document successes and failures, identify patterns, and iterate on prompts and workflows until optimal results are achieved.

• Customize Solutions for Beta Clients – Adapt and configure AI prompts and automation systems to meet specific beta client requirements, ensuring customizations align with their unique business contexts and operational needs.

• Document and Version Control Systems – Create comprehensive documentation for each automation workflow, including architecture diagrams, prompt chains, integration points, testing results, and versioning to enable reproducibility and future enhancement.

• Analyze Business Use Cases – Translate business objectives into technical automation requirements, ensuring workflows deliver meaningful value and align with founder and staff decision-making processes.

• Monitor and Optimize Automation Performance – Track output quality, relevance, and accuracy of AI-generated insights (e.g., trend spotting, scoring, database population), using feedback to continuously improve prompt engineering and system design.

• Collaborate on Product Development – Work directly with founders to refine the Company OS product, contributing insights from automation development that drive productization strategy during beta release.

• Research and Experiment with AI Capabilities – Stay current with LLM advancements, test emerging prompt engineering techniques, and propose innovative automation opportunities that enhance the Company OS intelligence layer.

Key Metrics

1. Automation Workflows Delivered – Number of functional AI automation workflows successfully built, tested, and deployed per month (internal and beta client).

2. Prompt Iteration Quality – Percentage improvement in output relevance, accuracy, and usefulness from initial prompt to final optimized version through systematic testing.

3. Documentation Completeness – Percentage of completed automations with comprehensive documentation including architecture, prompts, test results, and versioning for reproducibility.

4. Beta Client Customization Success – Number of client-specific automation customizations deployed successfully with positive feedback on business value delivered.

5. Testing Velocity – Number of prompt variations and workflow configurations tested per project, demonstrating thoroughness and experimental rigor.

6. Automation Reliability – Percentage of deployed automations running without errors or requiring minimal troubleshooting after launch.

7. Business Impact Score – Qualitative assessment (by founders) of how effectively automations deliver actionable intelligence that improves decision-making and operational efficiency.

8. Learning and Innovation Rate – Number of new prompt engineering techniques, LLM capabilities, or automation patterns discovered and proposed for integration into the Company OS.

Job Posting

AI Workflow Intern (Project-Based Internship)

What We're Looking For

Core Responsibilities

• Design and optimize AI prompts across multiple LLM platforms to generate intelligent, context-aware outputs from Company OS data

• Build automation workflows using scheduled triggers, webhooks, and integration platforms (Make.com, Zapier, n8n, etc.)

• Follow structured test plans to evaluate prompt and workflow performance, documenting what works and what doesn't

• Iterate systematically on prompts and workflows until target outcomes are achieved

• Customize AI automations for beta clients, adapting systems to their specific business contexts

• Create comprehensive documentation for each automation including architecture, prompts, test results, and version history

• Translate business use cases into technical automation requirements that deliver measurable value

• Research emerging LLM capabilities and propose innovative automation opportunities

Example Projects You Might Work On

• Trend Spotting Automation – Build deep-scan workflows that identify emerging trends relevant to a business, score them for fit, and populate a review database with AI-generated summaries and recommendations

• Executive Intelligence Briefings – Design prompts that synthesize data across tasks, metrics, and meeting notes to generate weekly executive summaries

• Client Onboarding Workflows – Create automation chains that customize Company OS setup based on client responses and business context

• Performance Alerts – Build intelligent monitoring that detects patterns in business metrics and generates contextual recommendations

Ideal Candidate

• Passionate about AI and excited to experiment with prompt engineering across multiple LLM platforms

• Strong understanding of how to communicate effectively with AI (basic to advanced prompt engineering)

• Business-minded: you understand why a workflow matters, not just how to build it

• Detail-oriented with a systematic approach to testing and documentation

• Curious and driven to achieve better results through continuous iteration

• Comfortable with Notion (or eager to learn quickly)

• Familiarity with automation platforms (Make.com, Zapier, n8n) is a plus

• Experience with APIs, webhooks, and JSON is helpful but not required

• Self-directed: you can take an objective and figure out the path forward with minimal hand-holding

This role is perfect for someone who wants to be at the intersection of AI and business operations. If you love experimenting with prompts, debugging workflows, and seeing your work directly impact how businesses operate—this is for you.

Internship Details

• Commitment: Part-time, project-based (10-15 hrs/week flexible)

• Duration: 3-6 months with potential to extend or convert to ongoing role

• Work Style: Remote with weekly check-ins directly with a founder

• Compensation: Stipend-based or course credit (depending on your situation)

• Learning Opportunity: Direct mentorship from founders with 20+ years scaling businesses; real-world AI product development experience

How to Apply

1. A short note on why you're excited about this role and what you hope to learn

2. Examples of any AI/automation work you've done (prompt engineering, workflows, side projects, coursework)

3. A description of your experience with Notion, LLMs, or automation tools

4. Your availability (hours per week, start date, duration)

5. Include the code word "Intelligence" at the top of your proposal so we know you've read the full description

Why Work With Us

• Advanced prompt engineering across multiple LLM platforms

• Automation architecture and workflow design

• Product development during beta release

• Business context and use case translation

• Direct founder mentorship and strategic thinking

About Modern Operators

• Damon Flowers has spent 20+ years building and scaling companies from early-stage to eight-figure outcomes. He is known for architecting operating systems, transforming chaotic teams into aligned execution machines, and mentoring founders and leaders through the transition from “doing everything” to building a company that grows beyond them. His work blends strategic clarity, operational structure, and the practical integration of AI into day-to-day workflows.

• Mark Malian brings 7+ years of experience in growth strategy, brand positioning, and systems automation inside agencies and product companies. His expertise lies in turning complex processes into clean, scalable systems…especially in marketing, sales, and customer operations, so teams can produce consistent pipeline, shorten deal cycles, and unlock predictable growth.