Senior AI Implementation Program Manager

Axiom Path•Bridgewater, NJ

4d•Remote

About The Position

This role leads delivery of enterprise AI-agent initiatives in a highly regulated pharmaceutical and life-sciences environment. The program manager works with Enterprise Applications leaders, business stakeholders, technical teams, and external implementation partners to take defined AI-agent use cases from requirements through development, testing, deployment, hypercare, and transition to support. The role initially owns two concurrent implementations, with scope expected to grow to approximately four. The position combines iterative Agile delivery with regulated-environment governance, validation, security, quality, and production controls. It includes coordinating cross-functional teams, maintaining delivery plans and accountability, resolving risks and blockers, and communicating status to leadership and stakeholders. The role is also expected to help improve the repeatable delivery model for future AI-agent initiatives and to step into delivery gaps as needed. This is a primarily remote opportunity, with onsite collaboration in Bridgewater, New Jersey approximately two to three times per month. The initial W2 contract is expected to run for approximately six months, with potential extension based on performance and the continued AI-agent roadmap.

Requirements

At least 7 years of IT project management, program management, or technology-delivery experience in complex enterprise environments.
Demonstrated experience delivering AI, Generative AI, AI-agent, intelligent automation, or similar emerging-technology initiatives.
Strong Agile/Scrum delivery experience, including hands-on facilitation of daily Scrum meetings, sprint planning, backlog refinement, reviews and demonstrations, retrospectives, and iterative release cycles.
Experience managing multiple concurrent technology initiatives with overlapping resources, dependencies, vendors, and stakeholders.
Technical fluency sufficient to work effectively with architects, engineers, developers, data teams, security teams, and implementation partners.
Working knowledge of AI-agent delivery concepts, APIs, integrations, enterprise data, identity and access, security, testing, monitoring, and production support.
Strong experience managing risks, issues, dependencies, decisions, actions, and delivery accountability.
Experience coordinating external vendors and implementation partners, including SOW commitments, milestones, deliverables, and escalations.
Strong communication, facilitation, and stakeholder-management skills.
Ability to operate independently after onboarding and organizational orientation.
Willingness to step beyond traditional project-manager responsibilities when delivery gaps need to be addressed.
Ability to travel onsite to Bridgewater, New Jersey approximately two to three times per month.

Nice To Haves

Personally managed AI-agent development or rollout initiatives.
Direct experience delivering technology programs in pharmaceutical, biotechnology, life sciences, or another GxP-regulated environment.
Experience with regulated delivery models involving validation, quality controls, governance, change management, auditability, compliance, or formal release processes.
PMP certification.
PMI-ACP, Certified ScrumMaster, SAFe, or similar Agile certification.

Responsibilities

Drive multiple AI-agent initiatives from defined requirements through development, testing, implementation, deployment, hypercare, and transition to support.
Manage two concurrent AI-agent implementations initially, with scope expected to grow to approximately four.
Lead Agile delivery activities, including daily Scrum meetings, sprint planning, backlog refinement, sprint reviews, demonstrations, retrospectives, and iterative feedback cycles.
Maintain delivery plans, milestones, sprint goals, dependencies, resources, risks, issues, decisions, actions, and accountable owners.
Partner with internal Enterprise Applications teams and external AI implementation partners to maintain delivery momentum and accountability.
Coordinate work across architecture, integrations, data, cloud and infrastructure, cybersecurity, privacy, AI governance, quality, and business stakeholders.
Incorporate regulated delivery requirements, governance checkpoints, testing, documentation, approvals, and production controls into project execution.
Identify blockers, technical dependencies, resource constraints, and delivery risks early, and drive them toward timely resolution.
Translate defined business outcomes into delivery plans, backlogs, user stories, technical tasks, and measurable success criteria.
Hold internal teams and external vendors accountable for sprint commitments, deliverables, timelines, and agreed decisions.
Support SIT, UAT, defect management, production readiness, cutover, deployment, hypercare, and transition-to-support activities.
Provide concise, action-oriented updates to leadership, PMO stakeholders, technical teams, and business sponsors.
Address delivery gaps beyond traditional project-management responsibilities when needed.
Continuously improve the operating model for future AI-agent initiatives.