AI Solutions Strategist

superset} Hive Community • San Francisco, CA

2d • Hybrid

About The Position

Fricative is building toward a Decision Management System, a way to bring together scattered information and external signals to help teams answer practical questions like 'What should we do, why, and why now?'. The system aims to provide answers that are not only persuasive but also transparent, showing the origin of claims, how evidence fits together, and what remains uncertain. The company is developing this system with real clients and real decisions, as it's a new category without an established playbook. Fricative is a portfolio company of superset, a venture studio that builds AI-native companies.

The AI Solutions Strategist role involves helping to write the playbook for this new system. The focus is on staying close to customer decisions, understanding their current processes, identifying blind spots, and gathering information from various sources, including public data and internal knowledge. The role will leverage AI to gather, test, and synthesize evidence at scale. A key aspect is translating messy problems into structured workflows, defining the roles of different AI skills, and ensuring the system produces reliable and useful answers. This includes identifying gaps and collaborating with engineers to close them. The ultimate goal is to deliver clear, sourced accounts of events, defensible recommendations, and actionable insights to clients, explaining the reasoning and gathering feedback for improvement. The role requires a blend of customer understanding, technical insight, research skills, and strategic thinking, with the ability to move between these modes while focusing on the decision-making process. The individual will be responsible for figuring out what the team should be building, rather than solely focusing on coding.

Requirements

• Experience taking an unclear business or customer problem, asking the right questions, and figuring out what actually needs to be solved.
• Ability to investigate across multiple sources, assess source quality, distinguish fact from inference, identify conflicting evidence, and explain what would change your conclusion.
• Experience working directly with customers or users to understand how they work, uncover needs that aren't obvious from the initial request, and turn those insights into action.
• Ability to think clearly and communicate clearly: separate what you know from what you believe, recognize uncertainty, challenge assumptions, change your view when the evidence changes, and explain complex work to different audiences.
• Enough technical understanding to work effectively with engineers and get hands-on with tools, data, APIs, automation, or AI without needing to be an engineer by training.
• Demonstrated use of AI tools to investigate, analyze, synthesize, prototype, automate, or solve a real problem.
• Experience turning an idea, hypothesis, or insight into something tangible, testing it with real users, and learning from what happens.

Nice To Haves

• A non-linear background that doesn't fit neatly into one discipline. Maybe you've worked in consulting, research, journalism, analytics, operations, product, or a technical customer-facing role. Maybe you've built something on your own.
• 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.

Responsibilities

• Understand the decision: Get close to the customer, learn how they make the decision today, what they know, what they're missing, and what constraints shape the choice.
• Investigate and frame the problem: Find and assess relevant internal and external information. Distinguish signal from noise and fact from inference, and make the alternatives, uncertainties, and implications clear.
• Design and build the workflow: Break the problem into the right skills and building blocks. Decide what each skill does, what it should never touch, what needs to happen before it runs, and how skills should feed into one another. Run samples, find failures and edge cases, and improve the system until the pieces work together reliably. Flag missing integrations or capabilities for engineers to build.
• Put working ideas in front of users, explain the reasoning, and learn whether they understand, trust, and act on them.
• Turn what works into a repeatable product and method for the next decision.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed