Senior Manager, Technical Program Management

Personally drive end-to-end delivery of multiple concurrent AI/workflow initiatives across BUs.

Run discovery, design, pilot, scale, and adoption phases using agile/lean methods.

Manage cross-functional pods comprising business SMEs, data scientists, AI engineers, designers, and change managers.

Own risks, dependencies, budgets, vendor management, and stakeholder communication.

Lead "as-is to to-be" workflow mapping using Lean, Six Sigma, and design-thinking techniques.

Identify automation, augmentation, and elimination opportunities; redesign processes to be "AI-native."

Partner with BU heads to redefine operating models, roles, and SOPs post-AI deployment.

Stay deeply hands-on with leading GenAI tools and platforms (e.g., ChatGPT/Enterprise, Microsoft Copilot, Google Gemini, Claude, GitHub Copilot, LangChain, LlamaIndex, vector databases, agentic frameworks, RAG architectures, low-code/no-code AI builders).

Personally prototype, demo, and pilot GenAI solutions—prompt engineering, custom GPTs/agents, workflow bots—before scaling.

Evaluate build vs. buy decisions; partner with AI/IT teams to operationalize solutions responsibly.

Maintain a working knowledge of model capabilities, limitations, cost, and Responsible AI considerations.

Drive end-user adoption through training, communications, and "AI champions" networks across BUs.

Co-create change management plans with HR and BU leadership; address concerns related to role evolution and reskilling.

Build internal capability through playbooks, reusable assets, and knowledge repositories.

Ensure all initiatives comply with data privacy, security, IP, and Responsible AI policies.

Partner with Legal, Risk, InfoSec, and Compliance to maintain guardrails for GenAI usage.

Establish review checkpoints for model risk, bias, and ethical implications.

Hands-on proficiency with GenAI platforms (ChatGPT Enterprise, Copilot, Gemini, Claude) and prompt engineering.

Familiarity with RAG, AI agents, automation platforms (UiPath, Power Automate, n8n, Zapier), and integration patterns.

Working understanding of LLMs, APIs, data pipelines, and AI governance frameworks.

Comfort with analytics and visualization tools (Power BI, Tableau).

Exceptional program management, structured problem-solving, and prioritization skills.

Strong financial acumen—able to build business cases and quantify ROI.

Outstanding executive communication, storytelling, and stakeholder influence.

Change leadership and the ability to drive adoption in resistant environments.

Hands-on operator's mindset—comfortable moving between strategy and execution.

Intellectually curious; continuously experiments with emerging AI tools.

Bias for action, outcome orientation, and high ownership.

Collaborative, low-ego, and able to thrive in ambiguity.

Month 3: PMO operating model, governance, and value-tracking framework established; cross-BU use-case pipeline built and prioritized.

Month 6: 3–5 high-impact GenAI/workflow pilots delivered with measurable productivity outcomes.

Month 9: Scaled adoption of top 2–3 use cases across BUs; reusable playbooks and AI champions network in place.

Month 12: Demonstrated enterprise-level efficiency gains (quantified $ savings / FTE productivity); AI-native workflows embedded into BAU; second-wave roadmap funded and underway.

This is a rare opportunity to shape and lead the AI transformation agenda of an entire enterprise. You will work directly with senior leadership, influence the future operating model of the organization, and play a defining role in how our people and processes evolve in the age of AI.

If you are a seasoned program leader who is equally excited by strategy decks and tinkering with the latest GenAI agent—this role is built for you

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