If you love building AI agents, wiring systems together, and watching entire teams stop doing by hand what a machine can do better, faster, and cheaper… and you want to make a whole company AI-native, not just ship a slick demo… then keep reading.

This is not a typical engineering role. You’re gonna be the person who makes Vidalytics AI-native, top to bottom. You’ll build the agents, the LLM chains, the prompts, the reusable skills, and the cross-system automations that let every team punch way above its weight. Reporting to the CEO. LFG!

You’ll start where the money is: the revenue teams (sales + marketing). Then you’ll take it across the whole org: finance, recruiting, product, engineering, and business intelligence. You won’t run out of things to automate, because you’ll keep standing up internal tools that keep making the company better.

This is NOT for you if… you’re a prompt dabbler, a demo-maker, or someone who needs a tidy spec handed to them. We don’t need someone learning the basics on the job. We need someone who’s already shipped this stuff in production and can do it here on day one.

We’re Vidalytics.com, a video hosting platform made for Video Sales Letters (VSLs), used by top direct response and performance marketers.

Videos hosted on Vidalytics have sold over $5.7 Billion. We aren’t some brand-awareness fluff factory. We’re ROI or Die.

Clients include:

VShred • Frank Kern • USCCA • Jon Benson • Primal Health • Brendon Burchard • Performance Golf • Todd Brown • Perry Belcher • Entrenation • Mike Dillard • Trugenics • Chris Haddad • And even bigger / better known brands that are under NDA

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• Build AI agents and LLM chains that do real work end to end, not chatbots that just talk.
• Write, version, and battle-test prompts like code. Build reusable skills the whole org can run.
• Stand up cross-system automations (n8n, Zapier, and custom code) that wire our tools together so work flows without a human babysitting it.
• Make the revenue teams (sales + marketing) AI-native first, because that’s where the money is. Then take it across finance, recruiting, product, engineering, and BI.
• Continuously ship internal tools and automations that keep making the company better. You’re never “done.”
• Build evals and observability so every AI system is measured, monitored, traced, and cost-controlled. If you can’t measure it, you can’t ship it.
• Ground AI outputs in our own company data (retrieval / RAG) so they’re accurate, not confidently wrong.
• Diagnose failures, kill hallucinations, and build the guardrails that keep systems reliable in production.
• Help with AEO / GEO where it moves the needle.
  
  

(The must haves)

• You’ve already shipped this kind of work in production. This is not a learn-on-the-job role. Because AI is a young field, we only expect a few years of hands-on AI experience, but it has to sit on top of strong, relevant broader experience, and you must have already built and run real AI systems that other people depend on.
• You’re fluent across the frontier models, with Claude as your primary. You know which model to reach for and why (cost, latency, context, reliability).
• You’re fluent in Claude Code and Claude Cowork, and you use them daily.
• You’re an expert at building reusable skills and at prompt engineering. You version and test prompts the way a serious engineer versions code.
• You can actually code. You’re comfortable around databases, APIs, and MCP, wiring systems together for real, not just clicking boxes.
• You’re comfortable with AI-native hosting and deployment (e.g., Vercel).
• You’re hands-on with automation tools like n8n and Zapier, and you know when to drop them and write custom orchestration instead.
• You ground AI outputs in real data with retrieval / RAG so they’re accurate and don’t hallucinate.
• You build evals and observability by default. You measure, monitor, trace, and control cost as a matter of habit.
• You hold a production-grade reliability bar. You ship systems that work and keep working for months, not demos that impress once and break the next day.
• Your working hours need to have a strong overlap w/ Eastern US time zone. Can discuss further.

Nice to Have 😃

(Not required, but a plus)

• Basic security and data protection know how. When you automate things, you don't want a free for all where anything can touch whatever data. Not a deal breaker.
• AEO / GEO experience.
• Deeper software engineering chops.
• Exposure to our stack: HubSpot, Fathom, Slack, Google Workspace, PostHog, Intercom, BigQuery, GCP, Vercel, v0, Lovable, Github.
  

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• You’re a passionate tinker who loves this field and playing with new tech, but you can also shut down your internal shiny ball syndrome and GSD (get shit done). 
• You translate between business problems and AI systems. You ask the right questions, fill the gaps, and turn messy business needs into working automations.
• You’re organized. You speak ROI. You’re familiar with marketing, sales and customer success workflows in particular as well as other functions of a modern tech company. 
• You're biased toward shipping fast. You deliver in small, valuable chunks that compound.
• You're loyal to outcomes, not hype. You don't care how cool the tech is. You care whether it saved time, made money, or removed a human bottleneck.
• You measure everything. Evals, cost, latency, reliability. If it isn't measured, it isn't real.
• You thrive on vague specs and can coordinate the rapid ideas of a choatic visionary. You can talk out ideas, bring structure to projects and don’t need everything spoon fed to you or spec’ed out in pretty user stories. 
  

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