Note: The job is a remote job and is open to candidates in USA. NiCE is a global leader in software solutions, specializing in AI and customer experience. They are seeking a Senior AI Project Manager to oversee customer-facing software and AI/GenAI projects, ensuring effective delivery and communication across teams.
Responsibilities
- Manage software and AI/GenAI delivery projects, ensuring alignment with scope, timelines, and customer expectations
- Build and maintain project plans, schedules, RAID logs, and core delivery documentation
- Communicate project status, risks, and dependencies to customers and internal stakeholders
- Support escalation handling with professionalism and timely follow‑through
- Coordinate cross‑functional teams through the project lifecycle
- Contribute to PMO best‑practice adoption and continuous improvement efforts
- Adjust project plans based on changing priorities or customer needs
Skills
- Manage software and AI/GenAI delivery projects, ensuring alignment with scope, timelines, and customer expectations
- Build and maintain project plans, schedules, RAID logs, and core delivery documentation
- Communicate project status, risks, and dependencies to customers and internal stakeholders
- Support escalation handling with professionalism and timely follow‑through
- Coordinate cross‑functional teams through the project lifecycle
- Contribute to PMO best‑practice adoption and continuous improvement efforts
- Adjust project plans based on changing priorities or customer needs
- 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 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
Company Overview
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