AI Transformation Manager

Job Summary

The AI Transformation Manager is responsible for leading the organization’s transition into an AI-first enterprise. This role involves identifying high-value AI use cases, managing the implementation of agentic workflows and LLM-based systems, and driving the cultural change necessary for employees to work alongside AI. You will not only manage technology but also lead the "Workforce Transformation," ensuring that AI investments result in measurable ROI and enhanced human potential.

Key Responsibilities

1. Strategic Planning & Roadmap Development

• Develop and maintain the Enterprise AI Roadmap, prioritizing use cases based on feasibility, cost, and business impact.
• Define KPIs for AI success (e.g., time-to-market reduction, cost-per-task optimization, or revenue uplift).
• Partner with senior leadership to align AI initiatives with the company’s 3–5 year growth goals.

2. AI Implementation & Orchestration

• Lead the deployment of Agentic AI (autonomous agents) and RAG-based (Retrieval-Augmented Generation) knowledge systems across departments like HR, Finance, and Customer Operations.
• Oversee the "Build vs. Buy" evaluation for AI tools, ensuring interoperability with existing tech stacks (e.g., Azure AI, Microsoft 365 Copilot, or proprietary LLMs).
• Manage cross-functional "Pods" consisting of data scientists, engineers, and domain experts to deliver pilot projects within 60–90 day cycles.

3. AI Governance & Ethics

• Establish frameworks for Responsible AI , ensuring transparency, bias mitigation, and data privacy (GDPR/CCPA/AI Act compliance).
• Monitor AI performance for "model drift" and accuracy, ensuring the system remains reliable and defensible.

4. Change Management & Enablement

• Design and lead "AI Literacy" programs to upskill the workforce, moving beyond basic prompting to advanced AI-human collaboration.
• Manage organizational resistance by communicating a clear value narrative and identifying "AI Champions" within business units.
• Redesign workflows to capitalize on AI-human "Centaur" models, where AI handles routine processing and humans focus on high-stakes strategy and empathy.

Job Requirements

Technical Skills & Experience

• Education: Bachelor’s degree in Business, Computer Science, or Data Science. An MBA or post-graduate degree in Digital Transformation is highly preferred.
• Experience: 6+ years of experience in Digital Transformation, Product Management, or Management Consulting, with at least 2–3 years focused specifically on AI/ML projects.
• AI Fluency: Deep understanding of Generative AI capabilities, LLM lifecycles, and Agentic Workflows . You don't need to be a coder, but you must be able to "speak engineer."
• Data Literacy: Proficiency in data strategy—understanding data pipelines, quality, and how "grounding" affects AI accuracy.

Tools & Certifications (Preferred)

• Certifications: Microsoft Certified: AI Transformation Leader, PMP, or similar.
• Tooling Knowledge: Familiarity with AI orchestration platforms (LangChain, Zapier Central), MLOps basics, and BI tools (Tableau, PowerBI).