Senior AI Strategist

AJAIA•New York, NY

12h•$150,000 - $250,000•Hybrid

About The Position

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.

Requirements

Four to seven years in a role where business judgment was the product: management consulting, corporate strategy, private equity or venture capital operating work, product management, or senior operating roles. Founders who have run a real business are welcome here.
Client-facing or executive-facing experience. You have presented a recommendation to people who could say no to it, and handled it when they pushed back.
AI systems you have taken into production, or close to it, and can talk about honestly, including what broke.
A track record of owning outcomes rather than deliverables. You can point to something that changed because you worked on it.
The ability to take an ambiguous, badly described situation and impose structure on it quickly.
Written and verbal communication that holds an executive room. You can compress a week of findings into one page and defend it under questioning.
Experience directing technical partners without managing them. You have set scope and success criteria for people who report elsewhere.

Nice To Haves

Experience in a regulated industry such as healthcare, financial services, insurance, legal, or education, and comfort with the governance that comes with it.
Process mapping or business process redesign at scale.
Working familiarity with workflow automation tools such as n8n, Zapier, or Make, and enough SQL or Python literacy to inspect data yourself.
Time inside a private equity or venture-backed operating environment.
Prior consulting at a firm where you carried a book or shaped scope, not only staffed to it.

Responsibilities

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.
Direct forward deployed engineers and analysts on your engagements. You own the problem, the sequence, and the definition of done. They own the build. Adoption is on all of you.
Prototype it yourself when a working demo settles the argument faster than a deck.
Present to the C-suite and to boards. One recommendation, the tradeoffs stated, a decision at the end of it.
Design the governance alongside the solution. Who approves, what data goes where, how output gets checked, and what happens when it is wrong. In regulated clients this is the part that decides whether anything ships.
Handle the hard client conversations: a missed date, a recommendation the sponsor does not want, a pilot that should be killed.
Grow the account. Spot the next problem worth solving and shape the work that follows.
Raise the people around you. Pressure-test an analyst's findings, sit in on a junior strategist's first CEO meeting, and make the second engagement better than the first.