AI Enablement Coach

AI Coach / Business AI Enablement LeadAtlanta, Georgia (Onsite)5 Days work from officeYears of experience: 12+ YearsPartner directly with business-function teams to identify use cases, map workflows, define KPIs, support adoption, and upskill business users. The AI Coach role is responsible for workflow mapping, ROI and KPIs, value realization, adoption support, and upskilling teams.This role is a key member of the AI Enablement Lab for rapidly enabling Agentic AI for core business functions while building the reusable foundation for developing, deploying, governing, and monitoring AI agents.The AI Coach partners directly with business-function teams to identify use cases, map workflows, define KPIs, support adoption, and upskill business users.Key responsibilitiesRun inception workshops with business teams.Document current-state process maps.Identify high-value agentic AI use cases.Define success metrics, ROI assumptions, and adoption goals.Help business teams redesign workflows around human-in-the-loop AI.Support pilot users, collect feedback, and drive adoption.Build prompt literacy and agent literacy across business teams.Identify role-level AI skills gaps as part of the paired engineering phase.Co-design AI agents with business and engineering teams to automate or augment workflows.Translate business processes into agent workflows, including task decomposition, decision logic, and tool usage.Define agent roles, boundaries, escalation paths, and human-in-the-loop controls.Collaborate with engineering teams on agent requirements, data needs, APIs, and integrations.Develop and iterate prompts, instructions, and evaluation criteria for AI agents.Establish guardrails for responsible AI use, compliance, and risk mitigation in agent design.Test, validate, and monitor AI agent performance against defined KPIs and business outcomes.Drive continuous improvement of deployed agents based on feedback, telemetry, and usage patterns.Skills requiredBusiness process mapping and facilitation.Design thinking and value-stream analysis.KPI and ROI definition.Strong communication and training skills.Familiarity with AI capabilities, limitations, and responsible-use practices.Change management and adoption planning.Ability to work with non-technical business stakeholders.Understanding of agentic AI concepts (multi-step reasoning, tool use, orchestration, memory, autonomy levels).Experience designing or contributing to AI agent workflows or automation solutions.Prompt engineering and prompt orchestration for task execution.Ability to translate business requirements into agent specifications and interaction flows.Familiarity with AI agent frameworks and platforms (e.g., Copilot Studio, LangChain, Semantic Kernel, or similar).Knowledge of API integration concepts, data flows, and system interactions.Ability to define evaluation frameworks for agent quality, accuracy, and reliability.Awareness of AI governance, safety, and risk controls specific to autonomous or semi-autonomous systems.