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AI Strategy Lead
Location
United States
Posted
92 days ago
Salary
0
Seniority
Lead
No structured requirement data.
Job Description
AI Strategy Lead
Skaled Consulting
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 blueprints covering conversation/task flow and integration points for the AI Builder. - 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. - 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. - 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. - Owns the client relationship and Collaboration in Delivery: Participate in key design review sessions. - Review intermediate outputs to ensure alignment with the original vision. - Support Testing & Iteration: Help define test scenarios and success criteria based on intended use. - Gather feedback on AI performance during user acceptance testing or pilot phases. - Client Sign-off/Engagement Management: Own the client relationship, contributing to scoping and value discussions. 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 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. - Collaboration Efficiency: Smoothness of project execution from a requirements/design standpoint. - Thought Leadership Output: Involvement in pre-sales and marketing efforts. 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 with the ability to identify unconventional but effective AI-based solutions.
Job Requirements
- 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 with the ability to identify unconventional but effective AI-based solutions.
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