AI Project Manager

AI PROJECT MANAGER

LOCATION:

SAN DIEGO, CA (HYBRID)

DURATION: 6-MONTH CONTRACT

PAY: 108-113 USD per hour

In this role, you will manage and support a portfolio of enterprise AI initiatives, driving projects from intake through pilot and production.

• Managing and prioritizing multiple AI initiatives across R&D, Commercial, Manufacturing, and Corporate functions, including:
• Enterprise search and conversational assistants.
• Document Q&A and document intelligence.
• Report drafting and meeting intelligence.
• Request triage and workflow automation.
• Agentic AI and multi-step automation capabilities.
• Sequencing an active AI roadmap against available team and pod capacity.
• Making and documenting prioritization decisions regarding initiatives that proceed, defer, or stop.
• Driving AI initiatives from intake through pilot and production, including scope, milestones, dependencies, risks, and launch activities.
• Removing blockers and coordinating delivery across small technical and business-focused pods.
• Leading the delivery of agentic AI and multi-step automation capabilities, including human-in-the-loop controls, escalation paths, guardrails, monitoring, and rollback provisions.
• Partnering with Legal, Security, IT, Compliance, and other stakeholders to ensure governance and approvals are incorporated into delivery plans.
• Managing implementation partners and SaaS vendors against SOWs, timelines, and committed deliverables.
• Developing and executing adoption plans for each AI capability, including pilot cohort design, utilization tracking, and user enablement.
• Preparing status updates, decision materials, and steering communications for VPs and executive leadership.

• Manage project delivery activities from initial intake through pilot and production deployment.
• Maintain project scopes, milestones, dependencies, risks, decisions, and launch plans.
• Establish and maintain a transparent prioritization model that connects business value, delivery requirements, and available pod capacity.
• Document and communicate roadmap changes, prioritization decisions, and scope adjustments.
• Coordinate AI Policy Review Committee submissions and ensure required governance activities are completed on schedule.
• Engage Legal, Security, IT, Compliance, and other governance stakeholders early in the project lifecycle.
• Evaluate AI workflows to determine which processes are appropriate for autonomous or agentic execution.
• Define human review checkpoints, escalation paths, monitoring requirements, guardrails, and rollback procedures for agentic AI solutions.
• Coordinate implementation across enterprise AI and automation platforms and technical teams.
• Monitor vendors and implementation partners to ensure delivery aligns with SOW requirements and committed timelines.
• Establish pilot programs and measure utilization and adoption against defined targets.
• Coordinate enablement activities alongside AI literacy initiatives.
• Track and report production adoption rather than relying solely on deployment or launch metrics.
• Develop executive-level status reports, decision documents, steering materials, and other communications.
• Establish delivery cadences, intake processes, and documentation practices that can be sustained by the internal team following completion of the engagement.

• Strong project management, delivery, documentation, communication, and interpersonal skills.
• Strong understanding of enterprise AI, generative AI, automation, and machine learning delivery.
• Practical experience with agentic AI workflows, including tool use, orchestration, multi-step execution, and human-in-the-loop controls.
• Working knowledge of enterprise AI and automation platforms such as Claude, Microsoft 365 Copilot, Glean, Power Automate, and UiPath, or comparable technologies.
• Ability to evaluate AI platform and vendor capabilities and translate technical concepts into practical business requirements.
• Understanding of data and analytics delivery, including how data readiness and platform architecture impact AI outcomes.
• Strong understanding of AI governance, risk management, security, compliance, and approval processes.
• Experience working with Legal, Security, IT, Compliance, and other cross-functional stakeholders.
• Strong vendor and stakeholder management skills, including experience managing SOWs and implementation timelines.
• Strong analytical, organizational, problem-solving, and critical-thinking skills.
• Ability to manage competing…