AI Senior Product Manager

NICE•Atlanta, GA

16h

About The Position

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. Senior Product Manager — Analytics Platform NiCE (NASDAQ: NICE) is transforming the world with AI that puts people first. When the world’s leading organizations want to automate customer engagements into proactive, safe, intelligent actions — from interaction to resolution — they turn to NiCE. Trusted by organizations across 150+ countries, NiCE CXone is the enterprise customer experience AI platform that orchestrates human and AI agents, automates service, and accelerates intelligent experiences at scale. NiCE is seeking a Senior Product Manager to join the Analytics Platform team within the Platform LOB. The Analytics Platform is NiCE’s internal AI service layer — the engines and data capabilities that power CXone. It produces AI services including real-time transcription, post-call transcription, TopicAI, sentiment analysis, and behavior models that NiCE application teams consume to build customer-facing products. The Analytics Platform does not sell directly to enterprises — but it operates with full commercial discipline. Success is measured primarily by the breadth of internal service adoption, the quality of services delivered, and the impact those services have on NiCE’s AI differentiation in the market. This is a senior individual contributor role requiring deep product management expertise, demonstrable capability in AI-native product development, and the ability to operate fluently across two customer relationships simultaneously: the internal NiCE application teams who consume Analytics Platform services, and the enterprise customers who use those applications and expect to engage directly with the capability expert behind them. The Senior Product Manager owns the strategy, roadmap, and prototype-driven discovery for their area of the Analytics Platform. They move from customer insight to working, validated prototypes — producing detailed specifications that feed directly into the development pipeline. They work alongside the developers who own spec-driven code execution, with full product management accountability across the service portfolio, internal adoption, and external customer engagement. The ideal candidate understands how platform-layer AI services create value — not just technically, but commercially. They know how to grow adoption within a product organization, how to engage enterprise customers as the subject matter expert on a capability that sits beneath the product they’re using, and how to keep a clear view of service costs without letting current AI economics constrain what they’re willing to try. They bring strong product instincts, hands-on AI capability, and the credibility to be in the room with both internal engineering teams and enterprise AI governance functions.

Requirements

8+ years of experience in software product management or a directly relevant role
Experience owning a product or service with clear adoption, usage, or commercial metrics — and a demonstrated track record of moving those metrics
Demonstrable experience engaging directly with enterprise customers as a technical subject matter expert, including with AI governance, risk, or data science functions
Demonstrable experience building AI-native product prototypes using AI tools, and running structured AI evaluation cycles
Experience producing detailed product specifications that enable downstream engineering execution with minimal back-and-forth
Experience with version control and basic development workflow sufficient to manage a prototype codebase (Git, repo structure, commit discipline)
Experience leading and influencing teams that do not report to you in a matrixed global organization
Demonstrated ability to grow adoption of a product or service within an organization — understanding what drives and blocks adoption, and how to move it
Cost awareness without cost constraint: able to track and communicate service economics clearly, while keeping current AI model costs in proper perspective — the technology is getting cheaper faster than any team can optimize it
Engages enterprise customers with technical depth and commercial credibility — equally comfortable discussing accuracy benchmarks, integration patterns, and business value
Excellent written and oral communication skills across technical and non-technical audiences
Writes precise, detailed specifications — the foundation on which developers execute spec-driven development
Strong cross-functional leadership and project management skills
Hands-on familiarity with LLM behavior: prompt design, output evaluation, and failure modes

Nice To Haves

Platform, infrastructure, or API-layer product management where the direct customer is an internal team or developer
Contact center, CX, analytics, or adjacent enterprise software
Conversational AI, virtual agents, or generative AI applications — particularly from the perspective of the shared AI services these features consume
AI governance considerations — data privacy, audit logging, and regulatory requirements (GDPR, CCPA) — as they apply to AI services consumed across multiple application teams
Agentic AI workflows and multi-step AI orchestration, and how they shape requirements for the underlying AI services

Responsibilities

Own the roadmap for an Analytics Platform service area — set direction, prioritize, and keep it current
Produce and maintain the service specification for each release — a precise, machine-readable document generated through the prototyping process that functions as the primary prompt for the developers executing the build
Own domain expertise for your service area: AI capabilities, competitive landscape, and real-world production performance
Identify which NiCE application teams should consume each service, understand what is blocking adoption, and drive the changes that unlock it
Track and grow the number of NiCE applications actively consuming each Analytics Platform service
Work with application PMs to ensure services are positioned, documented, and ready to integrate when they need them
Define and communicate the value proposition of each service to internal consumers: accuracy, latency, reliability, and ease of integration
Maintain visibility into the cost dimension of your service portfolio: understand unit economics and monitor cost per service unit delivered
Give internal consumers transparent cost and performance data to support informed adoption decisions
Engage directly with NiCE enterprise customers as the Analytics Platform subject matter expert — a primary participant wherever Analytics Platform capabilities are in scope
Join application PMs in customer meetings — keep the underlying AI capability accurately represented and route customer feedback directly to the roadmap
Build direct relationships with enterprise customers, particularly AI governance, risk, and data science functions
Turn enterprise customer insight into service requirements: performance gaps, emerging use cases, governance requirements, and integration patterns that only surface through direct engagement
Represent the Analytics Platform at customer-facing sales meetings, events, and user conferences
Validate ideas and test assumptions with real customers before engineering cycles begin
Use prototypes to generate specifications
Design and run structured evaluation cycles for AI outputs — establishing baselines, identifying failure clusters, iterating one change at a time, and documenting results
Apply AI tools across discovery, synthesis, spec writing, competitive analysis, and stakeholder communication