Associate Product Manager

weavix•Wichita, KS

About The Position

The Associate Product Manager joins weavix’s Product & Engineering organization and works alongside experienced Product Managers to turn field feedback into shipped features. This hands-on role is designed to grow into a full Product Manager position. The Associate Product Manager owns well-scoped features end to end, keeps engineering unblocked, and helps ensure releases are successfully delivered to customers, Customer Success, and Sales. The team works AI-first, using AI for research, writing, and building working prototypes that clarify what engineering needs to build. The role includes gathering customer and field insights, translating feedback and data into prioritized problems, supporting feature development and testing, and preparing launches and adoption materials. The Associate Product Manager uses AI tools to research, synthesize feedback, draft product documents, and build prototypes, while validating AI-generated work and packaging prototypes with clear flows, criteria, edge cases, and known gaps.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, Business, or a related field, or equivalent experience.
At least 2 years of experience in product management, business analysis, QA, software engineering, technical support, solutions consulting, or a similar role.
Technical fluency, including understanding the basics of how software is built, tested, and released, and comfort reading API documentation or asking engineers relevant follow-up questions.
Clear writing skills, including the ability to write user stories, release notes, and short decision memos.
Analytical habits and comfort pulling and interpreting data.
Demonstrated history of daily use of AI tools such as Claude, ChatGPT, or Copilot for research, writing, and analysis, with the judgment to check output for accuracy.
Ability to build a working feature prototype with AI-assisted coding or design tools.
Ability to follow through independently, raise risks early, and remain calm when priorities shift.
Willingness to travel to customer sites, including manufacturing plants, job sites, and distribution centers, up to 25% of the time.

Nice To Haves

SQL skills.
Experience in industrial or frontline sectors such as manufacturing, construction, logistics, or oil and gas, or firsthand familiarity with work on a plant floor or job site.
Exposure to products combining hardware and software, or to IoT, telecom, or mobile apps.
Experience with Jira, Confluence, or similar tools and Agile/Scrum teams.
Familiarity with enterprise B2B SaaS concepts such as SSO, admin permissions, APIs, and integrations.
Bilingual ability, especially in Spanish.
Side projects or internal tools built with AI coding assistants, or working knowledge of HTML, CSS, JavaScript, or React.
Experience prompting LLM APIs or shipping simple AI-powered features.

Responsibilities

Join customer calls, site visits, and ride-alongs with Customer Success and Field Solutions to observe how crews use Walt on plant floors and job sites.
Turn field tickets, support trends, usage data, and sales feedback into clear problem statements for prioritization.
Track competing radio and frontline communication products and summarize relevant findings for the roadmap.
Write and maintain user stories, acceptance criteria, and lightweight specifications for owned features in Jira.
Attend Scrum ceremonies with the assigned pod, answer product questions, and escalate trade-offs to the Product Team and Engineering Manager before they affect milestones.
Understand how features interact with Walt firmware, Cloud, Mobile, and Data to support integrated releases.
Test features in development, participate in QA reviews, and confirm shipped work meets customer needs.
Prepare release notes, internal enablement materials, and FAQs for feature releases.
Partner with Marketing, Sales, and Customer Success to help them explain and sell released features.
Define success metrics with the Product Manager and report on post-launch adoption.
Use AI tools to research customers, markets, and competitors; synthesize field feedback; and draft PRDs, user stories, and acceptance criteria, validating the output and owning the final documents.
Build clickable or working feature prototypes with AI coding and design tools to test ideas before engineering commits.
Package prototypes with user flows, demonstrated features, acceptance criteria, edge cases, and known gaps so engineers can build production versions.