backlog management process improvement for a startup
Project scope
Categories
Engineering project management Software developmentSkills
triage process improvement management software developmentQoherent is looking for a student intern to set up a system for managing our software development backlog and roadmap.
The student would take Qoherent’s desired feature list and translate it into a manageable and prioritized backlog in a tool such as Linear or Jira.
A successful project would result in Qoherent’s team of developers having a well curated and organized backlog, as well as a repeatable and measurable process for managing it.
- Review Qoherent’s products, development plans, and roadmap.
- Work with Qoherent team to identify and document components and layout of existing Qoherent software.
- Translate development plans into a task list.
- Set up an appropriate project in tracking software such as Linear or Jira
- Entry of relevant tasks, epics, and issues into the tracking software.
- Under guidance of Qoherent staff, triage and prioritize items in tracking software.
- Document methodology for adding, assigning, updating, and completing tasks.
- One-hour overview of Qoherent, and our business.
- One-hour live demonstration of our software.
- Recorded demonstrations of our software will be shared, and live demonstrations will be performed.
- One-hour review of the contents of select repositories as well a review of our software and components
- Weekly check-ins with Qoherent CEO to share progress, receive feedback, or review actions that are needed from Qoherent team.
- The CEO will be available via email.
About the company
Qoherent is an early-stage start-up that is driving the creation of AI-based radio technologies.
Qoherent provides solutions and a platform for integrating machine learning into software-defined radios, for the purpose of building robust, aware, and adaptive radio communication systems.
Qoherent’s current focus is on providing customers with software solutions for recognizing wireless activity with machine learning, as well as building a platform of software development tools to aid in creating machine learning models, deployable to heterogenous systems, that recognize radio waves.