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Executive Operations & Content Coordinator to Founder & CEO
Location: Colorado Springs, CO (In Person) Job Type: Full-Time Salary: $65,000–$80,000 annually, based on experience Schedule: Monday–Friday, with occasional travel and business events
About the Opportunity
We are seeking an exceptional, highly organized, tech-savvy professional to work directly alongside the Founder & CEO of multiple businesses spanning commercial roofing, business education, technology, and artificial intelligence.
This is not a traditional executive assistant position.
You will serve as the CEO's right hand, helping turn ideas into action, coordinate business initiatives, create social media content, organize events, and implement cutting-edge AI systems.
We are looking for someone who is proactive, resourceful, creative, and comfortable working in a fast-paced entrepreneurial environment. The ideal candidate can anticipate needs, take ownership of responsibilities, and execute without constant direction.
This is a unique opportunity to work side by side with an entrepreneur while gaining hands-on experience in business growth, executive operations, personal branding, and artificial intelligence.
Key ResponsibilitiesExecutive Operations & Project Coordination
- Work directly with the CEO to manage daily priorities, schedules, meetings, travel, and business initiatives.
- Turn ideas and conversations into actionable projects, assignments, and deadlines.
- Coordinate with employees, department leaders, and remote teams to ensure timely execution.
- Proactively follow up on commitments, monitor progress, and keep projects moving.
- Organize executive communications, business activities, and important information.
- Anticipate challenges, solve problems, and help maximize the CEO's productivity.
Social Media & Content Creation
- Capture authentic, behind-the-scenes video content of the CEO's daily business activities using a smartphone.
- Recognize valuable content opportunities and proactively record footage throughout the workday.
- Create, edit, caption, and publish engaging content for Instagram, Facebook, TikTok, and YouTube Shorts.
- Understand social media trends, storytelling, engaging hooks, and organic audience growth.
- Use tools such as CapCut, Canva, and AI-powered content creation platforms.
- Coordinate with the existing marketing and content team to support the CEO's personal brand.
- Organize content libraries and maintain a consistent publishing workflow.
Artificial Intelligence & Business Automation
- Work hand in hand with the CEO, who personally engineers and develops the organization's AI systems.
- Assist with implementing, testing, improving, and managing AI agents and automated workflows.
- Become highly proficient with the organization's AI tools and operating systems.
- Help integrate AI-powered systems into daily business operations.
- Research and test emerging AI technologies alongside the CEO.
- Assist with documenting processes and training employees on AI tools.
- Continuously expand your AI knowledge through hands-on implementation and ongoing learning.
Strong existing AI knowledge and a genuine passion for mastering emerging technology are essential. Programming experience is not required.
Events, Workshops & Business Activities
- Plan and coordinate business workshops, conferences, retreats, and special events.
- Organize venues, vendors, schedules, travel, registrations, and event logistics.
- Coordinate with speakers, attendees, and internal teams.
- Assist with podcast appearances, filming schedules, speaking engagements, and business events.
- Support event execution, preparation, and follow-up to ensure exceptional experiences.
Required Qualifications
- 3+ years of experience in executive support, business operations, project coordination, or a related role.
- Demonstrated experience organizing professional events, workshops, or conferences.
- Strong social media knowledge with hands-on experience filming, editing, and publishing short-form video content.
- Practical, professional experience using ChatGPT and other artificial intelligence tools.
- Exceptional organizational skills, communication, and attention to detail.
- Ability to independently manage multiple priorities and follow through on commitments.
- Strong technical aptitude and enthusiasm for learning new technology.
- Confidence working directly with a business owner or senior executive.
- Resourceful, proactive, adaptable, and comfortable in a fast-moving environment.
- Ability to work full-time, in person, in Colorado Springs.
Preferred Experience:
- Supporting entrepreneurs, founders, or executives.
- Creating content for a personal brand or business leader.
- Using CapCut, Canva, ClickUp, Slack, GoHighLevel, or similar platforms.
- Implementing AI agents, custom GPTs, or business automation workflows.
- Coordinating business conferences, educational workshops, or executive events.
The Ideal Candidate
You are someone who sees what needs to be done and takes action.
You are highly organized but also creative. You understand social media, enjoy learning technology, and can confidently manage multiple responsibilities.
You are comfortable capturing spontaneous video content, organizing an important event, learning a new AI system, and coordinating business priorities—all while staying focused on results.
You don't wait for constant instructions. You anticipate needs, communicate clearly, solve problems, and take pride in getting things done.
Most importantly, you want to work directly alongside an ambitious entrepreneur and become an essential part of building and growing successful businesses.
Why Join Us?
- Work directly with the Founder & CEO across multiple businesses.
- Gain hands-on experience with advanced AI systems and emerging technologies.
- Participate in business growth, content creation, professional events, and new initiatives.
- Take ownership of meaningful projects with opportunities for professional development.
- Join an entrepreneurial environment where initiative, creativity, and results are valued.
How to Apply
Please submit your resume and briefly answer the following:
- Social Media: Share examples of short-form videos or social media content you have personally filmed, edited, or published.
- AI Experience: What AI tools do you currently use, and what is the most advanced AI workflow or automation you've implemented?
- Event Coordination: Describe an event, workshop, or conference you helped organize and your role in its success.
- Executive Support: Describe your experience working directly with a founder, executive, or business owner.
We are looking for an exceptional individual who combines executive-level organization, creativity, strong AI capabilities, and the initiative to turn ideas into results.
Pay: $65,000.00 - $80,000.00 per year
Benefits:
- Paid time off
- Professional development assistance
Application Question(s):
- Describe your experience working directly with a founder or CEO. What responsibilities did you independently manage?
- Provide links to two short-form social media videos you personally filmed, edited, and published.
- Describe an AI workflow or automation you personally implemented. What tools did you use, and what did it accomplish?
Work Location: In person
Salary Context
This $65K-$80K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 1623 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Sean Moriarty | Founder Content, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($72K) sits 66% below the category median. Disclosed range: $65K to $80K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Sean Moriarty | Founder Content AI Hiring
Sean Moriarty | Founder Content has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Colorado Springs, CO, US. Compensation range: $80K - $80K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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