Lead Product Manager

As Lead Product Manager at NICE Cognigy, you will directly own AI Assist — the in-product AI copilot that scales across the entire CXone platform and every use case it supports — and you will lead across the broader Agent experience inside Cognigy (NICE's agent builder within CXone), including the agent building experience, traces, and the LLM platform. You set the direction, make the calls, and are accountable for outcomes end-to-end. You will report to the Director of Product.

This is a Lead role for someone who is already operating at this level today. You have run product streams independently, you set the bar for the PMs around you, and you bring an informed point of view on where the conversational AI space is going — because you are already building in it.

We are AI-first in how we build product. Prototypes over decks. Lighter PRDs, sharper artifacts. We ship our way to clarity rather than write our way there.

You will own AI Assist directly: vision, roadmap, delivery, and adoption across CXone. You will define what an in-product copilot needs to do for the full range of CXone users and use cases, ship it, and measure whether it actually changes how the platform gets used. Scaling AI Assist horizontally — across products, personas, and surfaces — is the core challenge of this role.

Across the wider Agent experience inside Cognigy, you will lead and align the teams shipping the agent building experience, traces, and LLM platform. You will set the joint direction, make the prioritization calls that span those teams, and ensure the surfaces feel like one product. You will partner with engineering and design as a technical peer, prototype your own ideas with modern AI tooling, and operate with the credibility to represent this scope to executive stakeholders.

You will set the bar for product craft on the team — how problems get framed, how PRDs get written, how decisions get closed — and you will raise the level of the PMs around you through example and direct partnership.

You are already a Lead PM, or operating at that level, in the conversational AI space. You ship in this domain today and have informed views on LLM-native vs. intent-based design, agent evaluations, RAG, prompting, and the trade-offs involved in building copilots and in-product AI assistants.

You are hands-on. You prototype your own ideas, experiment with new models and tools as they land, and bring that practical understanding into your product decisions. You can hold your own in architecture discussions with senior engineers.

You have strong product judgment, an ownership mindset, and the experience to operate independently in ambiguity. You make better decisions because of the people you work with, and they make better decisions because of you.

You are currently working as a Lead PM, or at an equivalent level, in conversational AI, LLM-enabled products, voice AI, or agentic systems. You have shipped at least one production product in this space and have hands-on experience with several of: copilots and in-product AI assistants, LLM gateways and routing, evaluations and observability, traces, embeddings and RAG, prompt engineering, or agent frameworks.

You have an enterprise SaaS background — multi-tenant, configurable, integration-heavy. You have led cross-functional initiatives with distributed, international teams, and you can point to product and business outcomes you owned.

If this matches your experience and ambitions, we encourage you to apply and share examples of products or decisions you owned end-to-end — what you decided, why, and what happened next.