NiCE - Senior Specialist Client Services Project Manager - AI

So, what's the role all about?

As a Senior Specialist Client Services Project Manager, you will be responsible for overseeing multiple projects and initiatives that support the organization's strategic goals. You will work closely with cross-functional teams to ensure successful project execution, on-time delivery, and adherence to quality standards.

How will you make an impact?

- Manage high visibility software and AI/GenAI projects, ensuring alignment with scope, timelines, and customer expectations.

- Manage project plans, schedules, RAID logs, and core project documentation.

- Provide consistent communication with executive leadership.

- Drive ownership, accountability, and escalation management.

- Guide teams through the full project lifecycle.

- Mentor project managers and support PMO best practice maturity.

Have you got what it takes?

- IT experience: 12 to 16 years

- 7 years of project management experience leading multiple concurrent projects in customer facing environments.

- Proven success delivering full lifecycle projects across Agile, Waterfall, and hybrid approaches.

- Experience delivering technical, SaaS, and AI/GenAI programs.

- Strong analytical skills with a track record of managing risks, revenue, and escalations.

- Excellent communication and expectation management skills.

- Advanced proficiency with tools such as MS Project, Salesforce, Rocketlane, and Power BI.

- PMP certification required.

AI Delivery (Preferred)

- Led endtoend delivery of conversational AI, LLM, and NLU solutions across scoping, execution, UAT, and deployment.

- Assessed AI use cases and evaluated data readiness, including ingestion, quality, labeling, and dependency tracking.

- Collaborated with engineering, product, R&D, and presales teams to validate model accuracy, output quality, and overall performance.

- Set and managed customer expectations while coordinating cross-functional delivery across technical and business teams.

- Identified and mitigated AI's pecific risks such as model drift, hallucinations, data issues, and expectation misalignment.

- Applied hands-on prompt engineering with a clear understanding of prompting limitations and optimization strategies.

- Leveraged AI tools in daily workflows for automation, data analysis, content generation, and quality validation.

- Defined and monitored AI performance KPIs, translating metrics (e.g., accuracy, containment, hallucination rate, latency, cost per inference) into actionable insights.

- Managed AI cost drivers, e.g. token usage, model selection, prompt structure, and architecture optimization for efficiency and performance.

- Ensured compliance with AI safety, governance, and security standards, implementing guardrails, redaction practices, and structured evaluation frameworks.

You will have an advantage if you also have:

- Experience working with Waterfall/Agile methodologies

- Experience with Onsite and offshore delivery model