AI Strategist
US$150,000 – US$250,000 / yr base salary
Posted 20 Aug 2026
Advertised as “Senior AI Strategist”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 4–7 yrs
- Management level
- People management
- Employment
- On-Site
- Contract
- Full-time
| Base salary | US$150,000 – US$250,000 / yr |
|---|---|
| Cash bonus | US$250,000 |
| Total comp | US$150,000 – US$500,000 |
Study levelBachelor's
About Ajaia
Ajaia is an AI implementation consultancy and product studio. We help organizations move from AI experimentation to measurable return on investment across four practices: AI Strategy and Advisory, Workforce Training and Enablement, Process Optimization, and Custom AI Development. Our work sits with executives and the people who do the actual work, and it is judged on whether something changed in production, not on whether a pilot looked good in a deck.
Position Overview
Ajaia is hiring a Senior AI Strategist to own client engagements end to end, from the first audit through a deployed system that people actually use. You will run the room with CEOs and their leadership teams, take apart how the work really gets done, and decide what changes, in what order, and what it is worth. You will direct Ajaia's forward deployed engineers and analysts on your engagements, and you will still be there at the end explaining why the number moved or why it did not.
Compensation: $150,000 to $250,000 base, plus a performance bonus of up to 100% of base salary.
How we expect you to work
AI use is a core execution requirement at Ajaia, not optional tooling. At this level you should have already put AI into production somewhere that mattered, dealt with what broke, and formed opinions about where the technology stops. Prompts that do real work, systems that run without you, models pointed at messy data where you checked whether the output was actually right.
The frontier moves weekly. Staying on it is part of the job, and so is being the person a client trusts to tell them which new capability matters to their business and which one is noise. You will be asked that question by people who have already been pitched by three vendors.
You will talk to an engineer on Tuesday and a chief executive on Wednesday about the same system. Both conversations have to land.
What you will do
- Own engagements end to end. Scope them, run them, and stay accountable for the outcome after go-live.
- Run AI audits inside client operations. Interview the CEO, the managers, and the people actually doing the work. Map how the business runs, not how the org chart says it runs.
- Find where the time and the money are going. Get a baseline before anyone claims an improvement.
- Decide what to fix first, and sequence it with owners, effort, and dependencies.
- Call what does not need AI. A required field, a template, or a named owner closes more problems than a model does, and part of your job is saying so to a client who wants to hear otherwise.
- Write the build spec your engineering partner works from: the outcome, the scope, the systems and data, where a human signs off, and how we know it is done.