[Hiring] AI Strategist @Supplied Talent

Role Description

The AI Strategy Lead is the chief architect of use-cases and AI solution logic within the practice. This person’s purpose is to identify, scope, and design intelligent assistants and agents that solve specific business problems, ensuring that each solution has a sound strategy behind it.

What You’ll Do Here

• Translate business objectives and pain points into concrete AI use-case definitions and agent logic.
• Serve as a bridge between business needs and technical execution.
• Act as the main point of contact for Skaled customers.
• Work closely with the Practice Lead on vision and support go-to-market (GTM) efforts.
• Collaborate with the Program Manager to ensure use-cases are delivered as envisioned.

Key Responsibilities

• Use-Case Discovery & Scoping:
  • Engage with clients and internal stakeholders to uncover high-impact opportunities for AI assistants or agents.
  • Conduct workshops or interviews to understand business processes (especially in RevOps/GTM areas like sales, marketing, customer success).
  • Define clear use-case statements including objectives, boundaries, and expected benefits.
• Solution Design & Agent Logic:
  • Design the AI agent’s logic and ROI in detail for each approved use-case.
  • Outline how the assistant/agent will function, including triggers, data usage, steps performed, and user/system interactions.
  • Create a blueprint for the AI Builder covering conversation/task flow and integration points.
• Feasibility Assessment:
  • Work closely with technical team members to vet the feasibility of proposed solutions.
  • Ensure ideas are realistic given current AI capabilities and the client’s tech environment.
  • Balance ambition with practicality, iterating on design until it’s impactful and achievable.
• Business Case & Value Definition:
  • Articulate the expected business value of AI solutions in real ROI terms for Skaled clients.
  • Quantify or qualify how the assistant/agent will improve outcomes.
  • Create ROI estimates or business cases that justify the project.
• GTM Support & Thought Leadership:
  • Contribute to sales and marketing efforts by providing the strategic vision for AI offerings.
  • Develop example use-cases for proposals and demo AI assistant concepts to prospective clients.
  • Author points-of-view on how AI can transform RevOps.
• Owns the client relationship and Collaboration in Delivery:
  • Participate in key design review sessions and clarify AI functionalities.
  • Review intermediate outputs to ensure alignment with the original vision.
  • Assist in making decisions about scope adjustments based on client requests.
• Support Testing & Iteration:
  • Help define test scenarios and success criteria based on intended use.
  • Gather feedback during user acceptance testing or pilot phases.
  • Work with the team to adjust prompts or logic rules if the AI isn’t delivering as expected.
• Client Sign-off/Engagement Management:
  • Own the client relationship, contributing to scoping and value discussions.
  • Handle client escalations beyond the solution scope with the Practice Lead or Program Manager.

Success Metrics

• Effective Use-Case Conversion: Number of identified AI use-cases that successfully move from idea to delivered solution.
• Business Impact of Solutions: Actual outcomes achieved by the AI assistants/agents relative to expected benefits.
• Client Satisfaction & Recognition: Feedback from clients regarding the quality of solution vision or logic.
• Innovation & Reusability: Introduction of novel or improved AI approaches and reusable templates.
• Collaboration Efficiency: Smoothness of project execution from a requirements/design standpoint.
• Thought Leadership Output: Involvement in pre-sales and marketing activities.

Qualifications

• 7+ years of experience in a consulting or solution architecture role (e.g., Solutions Architect, Business Analyst, or AI Strategist).
• Solid domain knowledge in Revenue Operations (RevOps) or Go-to-Market (GTM) processes.
• Up-to-date, practical knowledge of AI and Large Language Model (LLM) capabilities.
• Strong analytical thinker and communicator, skilled at breaking down complex business processes.
• History of creative problem-solving and framing unconventional AI-based solutions.