Data & Analytics AI Lead – Agentic & Conversational AI Professional

At IBM, we believe technology shapes the world. We’re a catalyst for that innovation. We’re driving change that improves businesses, society, and the human experience. Our Marketing, Communications & Corporate Social Responsibility (MCC) team tells this story. We shape IBM’s brand, capture attention in the market, and share our perspective with clients, partners, the media, and fellow IBMers. On our team, you’ll work with bright, collaborative minds who bring passion and creativity to everything they do.

You’ll be part of a culture built on openness, trust, and teamwork. Where your ideas matter and your growth is supported. Join us, and help bring innovation to life.

We are building a small, elite AI strike team embedded in the Marketing, Communications, and CSR (MCC) Strategy & Operations team. The mission is to move fast, explore what’s possible with agentic and conversational AI, and prove value quickly—before anything is scaled or productionized elsewhere.

This role leads that squad.

You will be a hands‑on AI leader with deep expertise in Large Language Models, conversational AI, and agent design. You will guide rapid experiments, build compelling proof‑of‑concepts, and help senior marketing leaders understand how AI can meaningfully change how work gets done.

This is not a traditional AI platform role, a reporting function, or a research lab. It is a high‑judgment, rapid‑execution role optimized for learning, momentum, and decision‑making.

• A hands‑on leader for a small, elite AI delivery team
• Focused on agentic AI, conversational experiences, and copilots
• Oriented around workflow transformation, not tools for their own sake
• Optimized for speed, experimentation, and proof‑of‑value
• Embedded directly in MCC Strategy & Operations Team
• Closely partnered with senior Marketing, Communications and CSR leaders

• A research‑only or theory‑heavy AI role
• A large team or program management position

• Lead a small, high‑trust AI squad focused on rapid delivery
• Set clear, time‑boxed missions with explicit learning or go/no‑go outcomes
• Balance hands‑on building with technical direction and coaching
• Optimize for progress and insight, not polish or permanence
• Apply deep understanding of LLM capabilities and constraints, including tokenization, context windows, latency, cost trade‑offs, failure modes, hallucination risks, and conversation state management
• Create flows that balance strong UX, deterministic logic, and LLM flexibility
• Design systems that translate user input into confident routing decisions using intent detection, semantic similarity, and hybrid triage approaches
• Decompose complex requests into actionable subtasks and orchestrate agents based on role, context, confidence, and history
• Build fallback paths, confidence scoring, and uncertainty handling, and implement guardrails to prevent unsafe, incorrect, or misleading behavior
• Lead hands‑on experimentation with proven agent patterns such as Router/Dispatcher, ReAct, Tool‑calling agents, and Retrieval‑Augmented Generation (RAG)
• Make pragmatic choices between prompt‑driven and code‑driven controls, optimizing for predictable, explainable behavior
• Design agents that are credible and trusted in an enterprise marketing context
• Develop advanced system, developer, and user prompt architectures, create prompt templates for routing, planning, classification, and tool use, manage prompt versioning and experimentation, and use constraints, grounding, and structured outputs to reduce hallucinations
• Iterate quickly based on live usage and feedback
• Ensure experiments consider safety, bias, explainability, and privacy while applying governance thoughtfully, without slowing experimentation
• Implement basic logging, evaluation, and traceability, and communicate risk, limitations, and trade‑offs clearly to stakeholders
• Translate marketing strategy and business needs into focused AI experiments, partner with senior marketing leaders as a thought partner and guide, clearly explain what AI can and cannot do—without hype, and help leaders decide what to pursue further, what to iterate, and what to…