Senior AI Project Manager, CX
RemoteUnited States
Job Summary
Manage software and AI/GenAI delivery projects from initiation through closure, ensuring alignment with scope, timelines, and customer expectations. Build and maintain project plans, schedules, RAID logs, and core delivery documentation while communicating status, risks, and dependencies to stakeholders. Coordinate cross-functional teams through the project lifecycle, support escalation handling, and adjust plans based on changing priorities. Contribute to PMO best-practice adoption and continuous improvement efforts, utilizing AI tools for automation and analysis. Assess AI use cases, partner with technical teams on model performance, and track AI-specific risks like data issues and hallucinations. Monitor and report AI performance KPIs, considering cost drivers and governance basics. Requires 5+ years managing customer-facing software projects with Agile or hybrid experience.
Required Qualifications
- 5+ years managing customer‐facing software or SaaS delivery projects
- Experience delivering projects across Agile, Waterfall, or hybrid methodologies
- Exposure to technical, SaaS, and/or AI/GenAI project environments
- Strong problem‐solving and risk‐management abilities
- Effective communication, organization, and stakeholder‐engagement skills
- Proficiency with project management tools (MS Project, Salesforce, Rocketlane, Power BI)
Desired Qualifications
- AI Delivery Experience (Preferred)
- Manage software delivery of conversational AI, LLM, or NLU projects
- Ability to assess AI use cases at a basic level and support evaluation of data readiness
- Partner with technical teams to understand model performance and output quality considerations
- Support customer expectation‐setting across AI/GenAI implementations
- Help identify and track AI‐specific risks (e.g., data issues, model behavior, hallucinations)
- Familiarity with prompt engineering concepts and prompting limitations
- Use AI tools in daily work for automation, analysis, or documentation
- Assist with monitoring and reporting AI performance KPIs
- Awareness of AI cost drivers such as token usage and model selection
- Understanding of AI governance and safety basics, including guardrails and data‐handling practices
- PMP certification preferred
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