AI Strategy and Delivery Lead

Bridge Atlantic•New York, NY

6d•Remote

About The Position

AI is easy to pilot and hard to embed. This role exists to close that gap. We're looking for an individual who can walk into a room of senior stakeholders, gain alignment on what AI should and shouldn't do, then make sure the resulting tools are adopted, governed, and trusted by the people using them every day.

Requirements

You've been a Lead or Product Owner who has actually deployed enterprise technology, not just written specs for it.
You know AI well enough to be useful, not just conversant. Generative AI, copilots, agents, automation, LLMs: you understand what they're good at and where they break down.
You've operated in messy organizations. Global, multi-stakeholder, competing priorities: you know how to build consensus when you don't have authority to just mandate a decision.
You can run agile delivery without needing someone else to manage the process.
You can hold your own on governance. Data privacy, security principles, and the practical realities of managing AI risk in a regulated or reputation-sensitive environment.
Temperamentally. This role rewards people who are pragmatic over perfectionist, genuinely comfortable in ambiguity, build relationships, and able to simplify without dumbing down.
You'll need the judgment to know when to push and when to listen, and the confidence to challenge leadership when the data says something different than what they expect.

Responsibilities

Sets the direction. Works with leadership to figure out where AI creates real value across the organization, then turns that into a prioritized, realistic roadmap, weighing impact against risk, complexity, and whether teams are actually ready to change how they work.
Gets the org to move. Many organizations are complex, global, and matrixed, which means this role can't rely on top-down authority. Success looks like building genuine agreement across business units, IT, HR, and other internal departments. Running the workshops, doing the translation between technical and business language, and designing the training and change management that makes adoption stick.
Deploys and governs. Owns the backlog, facilitates user story development, manages the pilots-to-scale pipeline, all while making sure everything that goes live meets the bar on ethics, privacy, legal, and security. This includes staying ahead of the risks that come with the territory: bias, deepfakes, data leakage, and third-party exposure. Underneath these layers lies a constant thread of measurement. This role is accountable for proving AI is working, not just that it's deployed. That means real KPIs, usage data, and regular reporting to leadership and governance forums, not vanity metrics.