AIA Transformation Lead - US Commercial (Secondment - 6 months)

Pfizer•New York City, NY

4d•Hybrid

About The Position

The AI Transformation Lead is a 6-month secondment role focused on identifying, designing, and scaling fully agentified workflows across the US Commercial organization. The role takes end-to-end accountability for transformation opportunities — from spotting workflows ripe for agentification, through mapping current-state processes, envisioning futureways of working, aligning stakeholders, and ensuring AI builds support the needs. Sitting within the US AI Commercial organization, this role is the connective leader between strategy, delivery, and adoption. The right person can see how work actually gets done today, imagine how it should get done tomorrow with agents in the loop, and bring leaders, teams, and technical partners along for the journey.

Requirements

12+ years of progressive experience in transformation, operations, strategy, or AI/ML with hands-on experience leading complex change end-to-end
Working knowledge of modern AI/ML and agentic AI capabilities — sufficient to credibly shape design, evaluate trade-offs, and challenge technical approaches
Demonstrated experience driving process redesign, operating model change, or workflow transformation in a complex, matrixed organization
Strong process mapping and analysis skills, — able to get into the detail of how work happens and translate it into design inputs
Strong executive presence and ability to align stakeholders and influence senior leaders without formal authority
Excellent strategic thinking, communications, and change management skills
Track record of managing cross functional teams, partnering with technical teams, business stakeholders, and executive sponsors
Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.
Permanent work authorization in the United States.

Nice To Haves

Advanced degree in a quantitative, technical, business, or organizational discipline
Pharmaceutical, healthcare, or life sciences industry experience, particularly within commercial functions
Direct experience designing, implementing, or scaling agentic AI solutions or AI-enabled workflow transformation
Familiarity with US Commercial functions such as marketing, omnichannel, field, patient services, or forecasting
Prior experience leading change at the SD/VP level

Responsibilities

Identify workflows ready for full agentification: Scan across US Commercial to identify workflows where agentification is feasible, valuable, and ready to pursue. Build a defensible point of view on which workflows to pursue first based on impact, complexity, readiness, and stakeholder appetite. Translate transformation opportunities into clear, decision-relevant proposals with defined sponsors, scope, and success measures.
Map current processes: Lead deep current-state process mapping for prioritized workflows, documenting the steps, hand-offs, decisions, data, and exceptions that make up the work today. Surface the underlying logic, dependencies, and judgment calls that any agent will need to replicate, replace, or escalate. Distinguish what is essential to the work from what is artifact of how it has historically been done.
Align stakeholders, manage communications and strategy: Build alignment across senior leaders, technical partners, and business teams on the transformation vision and path. Develop and own the communications strategy for each transformation: narrative, milestones, change story, and stakeholder cadence. Anticipate and address concerns proactively, building trust through clarity and consistent follow-through.
Ensure the build fits into the new workflow: Partner closely with AI Commercial Technical & Delivery Leads to ensure agent design meets the need to deliver on success metrics. Pressure-test prototypes against current-state realities, refining the design before scaled rollout. Drive integration with the surrounding people, process, and tooling so the build lands as part of a working system.
Scale across other teams: Once an agentified workflow is proven, drive its adoption across additional teams, brands, or functions where similar work exists. Codify what worked into reusable playbooks, change templates, and adoption patterns so future transformations move faster. Champion adoption.