Specialist Client Services Project Manager

At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you.

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.

Willingness to work in US shift (5 PM – 2 AM IST)

AI Delivery (Preferred)

Led end‑to‑end 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‑specific 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.