Product Manager, Qnect IQ / Quanta (Semantic AI Layer)

Quorum Software•Houston, TX

1d•Hybrid

About The Position

Quorum Software is seeking a Product Lead to shape and bring Qnect IQ / Quanta, its contextual and semantic AI layer, to market. The product brings together documents, events, and data from Quorum’s data platform, connects information to the business entities and concepts it describes, and makes that context useful to people, applications, and AI agents. The role owns product direction, customer discovery, priorities, and go-to-market execution in partnership with engineering and commercial teams. The Product Lead will turn an existing product and broad set of capabilities into focused customer experiences, identify valuable problems to solve, determine what to deliver, and measure customer usefulness and willingness to pay. This is a hands-on position in a small team, involving customer conversations, workflow exploration, demonstrations and prototypes, requirements writing, feature testing, and helping customers realize value. The role calls for experience in a startup or similarly small product team and comfort spanning product strategy and delivery details. The position is based in Houston, Texas (preferred), or anywhere in the United States. It is hybrid for employees located in Houston and remote with travel for employees elsewhere in the United States. Salary is $100,000–$176,900, commensurate with experience, with bi-weekly pay via direct deposit. Employment eligibility to work in the United States is required; the company will not pursue visa sponsorship. The successful candidate must complete criminal history, education, employment, driver’s license, and passport/ID verification checks.

Requirements

Experience owning a B2B software product or significant product area from discovery through delivery, launch, and customer adoption.
Experience in a startup or small product team, with direct responsibility for defining the product and helping bring it to market.
Strong customer discovery skills, including turning interviews, workflow observations, and usage evidence into clear product decisions.
Ability to work closely with engineers on APIs, integrations, data flows, and technical tradeoffs, and translate those details into customer-facing outcomes.
Practical understanding of AI-enabled products, including how data quality, context, retrieval, model limitations, permissions, and cost affect user experience.
Experience defining requirements and acceptance criteria, prioritizing a backlog, and validating delivered functionality with users.
Experience developing product positioning, supporting demonstrations and launches, and working with commercial teams to validate demand.
Ability to select meaningful metrics, interpret results, and adjust direction when evidence challenges an assumption.
Hands-on use of AI tools for product research, analysis, prototyping, or delivery, with judgment about how to validate their output.
Clear written and verbal communication, independent judgment, and ability to work through ambiguity across a distributed team.
Employment eligibility to work in the United States; visa sponsorship is not available.

Nice To Haves

Experience with enterprise search, document intelligence, knowledge management, semantic data, or AI agents.
Experience with event-driven products, data platforms, APIs, or shared capabilities used by multiple applications.
Experience with consumption-based pricing, AI credits, or the economics of AI-enabled services.
Experience building functional prototypes using AI coding tools or working directly with APIs and data.
Familiarity with energy-sector workflows or enterprise software for the energy industry.

Responsibilities

Own product direction and the roadmap, balancing customer value, commercial opportunity, engineering capacity, and dependencies across Quorum’s ecosystem.
Work directly with customers, users, and internal product teams to understand workflows, validate problems, and identify where connected information and AI can improve work.
Select focused use cases for pilots and early releases, define success criteria, and use feedback and observed usage to determine what to expand, change, or stop.
Define product requirements, user journeys, and acceptance criteria, and work with engineering to prioritize and deliver features that meet customer needs.
Shape capabilities across ingestion, document extraction, contextual relationships, search, cited answers, and knowledge access for applications and agents.
Build prototypes and demonstrations, review delivered features, and coordinate customer onboarding and feedback with engineering, QA, and Customer Success.
Lead product positioning and go-to-market planning with Sales, Marketing, and Customer Success, including target use cases, value propositions, demonstrations, and launch materials.
Work with commercial and platform teams on packaging, pricing, and AI-credit usage, balancing customer value with the cost of delivering AI capabilities.
Define and track product outcomes, including activation, successful task completion, repeat usage, customer value, consumption, and willingness to pay; use evidence to guide priorities.
Coordinate dependencies and launch readiness with platform, data, security, and operations teams, including access permissions and customer-data handling.
Communicate priorities, progress, decisions, and risks clearly to customers and internal stakeholders.
Perform other duties as assigned.