AI Solutions Strategist

The posting, as super{set} Hive Community wrote it

Format: In-office 4 days a week with flexibility for the occasional remote days

Fricative Mission

Businesses make consequential decisions with an incomplete view of the world.

What to invest in. Which customers to pursue. Where a market is moving. What risk to take. What to do next.

Their own information is scattered across systems, spreadsheets, conversations, and people’s heads. Meanwhile, public filings, market activity, company announcements, and other outside signals may reveal that something important has changed. People spend enormous amounts of time piecing this together, but the reasoning behind the eventual decision often remains invisible.

Fricative is building toward a Decision Management System: a way to bring those signals together and help a team answer a practical question: What should we do, why, and why now? The answers have to be more than persuasive. People should be able to see where each claim came from, how the evidence fits together, what remains uncertain, and what would change the recommendation. We’re developing this with real clients and real decisions because this is a category that doesn’t have a playbook yet.

Fricative is a portfolio company of super{set}, a venture studio that conceives, funds and builds AI-native companies from formation through scale. We work alongside founders as operators, helping shape companies from day one.

The Role

There isn't an established AI Solutions playbook to follow. You'll help write it while doing the work. The best way to build this system is to stay close to the decisions our customers are actually trying to make. You'll get close to a client's business, learn which decisions matter, how they make them today, and what they can't currently see. You'll draw out what different people know, notice where their accounts conflict, and earn enough trust to get past the polished version of how things work.

You'll investigate relevant public sources, find signals worth paying attention to, and connect them with what the client knows internally. You'll use AI to gather, test, and synthesize evidence at a scale that would be difficult to manage manually.

You'll turn the work into something a system can actually do. That means breaking a messy problem into the right building blocks, deciding what each skill should and should not do, and stitching those skills into a workflow that produces a useful answer. You'll test the workflow against real examples, find where skills fail, overlap or contradict each other, and tighten the system until it works reliably. When something requires an integration or capability the system doesn't have, you'll know enough to surface the gap and work with engineers to close it.

Then you'll turn that work into something useful: a clear, sourced account of what is happening, a defensible recommendation, and a way for
[…]
igated it, formed a view, built or tested something, changed your mind when the evidence changed, and made the result useful to someone else. You've probably experienced one or more of these:

• Work in financial institutions or other information-intensive enterprises.
• Complex or high-stakes business decisions.
• Working across internal data and external or public information sources.
• Using AI to change a research, analysis, or customer workflow.
• Working with APIs, data, software systems, automation, or technical products.
• Translating customer problems into product or technical requirements.
• Working in an early-stage company or another environment without an established playbook.
• Building something that moved from a one-off solution to a repeatable product, workflow, or method.

We want to see examples where you: Found the real problem. Investigated it. Formed a view. Built or recommended something. Tested it. Changed your opinion. Made the result useful to someone else.

Compensation

USD 150,000 - USD 200,000 annual base salary. The final offer will depend on qualifications, experience and location. This role is also eligible for equity.

The Opportunity

• Build a category around a new kind of system for managing how organizations make consequential decisions.
• Work directly with customers and the people building Fricative, using real decisions and real problems to shape what the product becomes.
• Partner directly with builders and operators who have repeatedly conceived, built and scaled category-defining infrastructure companies, learning from their pattern recognition while shaping Fricative alongside them.
• Shape the product and company from an early stage, with the autonomy to follow a problem wherever it leads and the support of a venture studio built to conceive, fund, and build AI-native companies.

If you've ever found yourself looking at a messy problem and thinking, “There has to be a better way to figure this out.” Let's talk.