Product Manager, Agentic Forecasting & Workforce Intelligence

Crescendo.ai•, (Multiple States)

5d•$150,000 - $250,000•Remote

About The Position

Crescendo is an AI-native contact center platform and CX operator for hundreds of enterprise clients. As part of this product offer, Crescendo is researching agentic approaches to workforce management. Specifically, the most advanced LLM AI technology to consider operational data and produce CX forecasts, staffing plans, CSAT predictions, and labor cost projections. We’re looking for a high agency technical Product Manager with Workforce Management (WFM) experience who is comfortable collaborating with operational leaders and also uses agentic coding tools to build software. While supported by an elite agentic engineering team for scalable and secure product delivery, this product manager would be building a fully working first pass of this system. This product will include agents to gather and organize operational data from multiple sources including the Crescendo technology platform as well as other IT systems such as time clock, HR, and finance software. This data will be consumed by a newly created WFM service that will produce forecasts and agent schedules for all Crescendo people operations. This service will also be available to enterprise customers to employ their own CX staff and use Crescendo as a technology-only service. As a Crescendo Product Manager you would work closely with engineering and interface directly with operations leadership for Crescendo as well as various functions including IT. If you’ve worked with WFM systems and want to help reinvent this software with an AI-native delivery model, this role is for you.

Requirements

Direct Workforce Management experience is required
Supporting capacity planning in CC / BPO environments
Working with Erlang-based staffing logic
Designing staffing models across queues or programs
Supporting intraday planning or long-range forecasting workflows
Implementing or integrating WFM platforms
Experience with systems such as: NICE, Verint, Genesys, Calabrio, Aspect, or equivalent WFM environments
You don’t need to be a full-time engineer—but you do need to be a builder and LLM AI enthusiast as this technology drives our product strategy.
Writing code using AI developer tools (Codex or Claude)
Working directly with structured datasets
Prototyping forecasting workflows
Translating operational logic into executable automation
Partnering closely with data science teams
Technical product management
product engineering
applied analytics platforms
AI-enabled operations tooling

Nice To Haves

Built forecasting or staffing tools inside WFM platforms
Supported CX or BPO delivery environments
Owned capacity planning infrastructure
Worked on workforce analytics platforms
Implemented WFM integrations
Built internal automation around staffing workflows
multitenant staffing models
agent-based workflows
planning automation assistants
AI-enabled scheduling or forecasting tools

Responsibilities

Build automated volume forecasting from Crescendo operational datasets
Translate forecasts into staffing and headcount requirements
Improve forecast accuracy through agentic self-improvement
Design staffing logic supporting shared associates across partner programs
Model cross-program capacity allocation
Enable dynamic queue balancing across workloads
Define how forecasts drive operational decisions inside Crescendo
Build AI-first workforce planning workflows
Move workforce planning from manual scheduling toward automation
Connect forecasting to full Crescendo IT stack: CRM/CC, HR, Finance.
Connect data collection agents to every major CCaaS and ticketing platform.
Build a closed feedback loop on forecast accuracy and schedule adherence.
Prototype workflows using AI developer tools
Build lightweight services, scripts, and assistants (week, not months)
Experiment with frontier models to evaluate best LLM model and agentic loop to perform WFM