Product Owner

Incident IQ•Atlanta, GA

10d•Hybrid

About The Position

At Incident IQ, we are reinventing how software gets built. In our Full Stack Agentic Development (FSAD) model, engineering capacity is no longer the bottleneck, context is. The Product Owner is the person who eliminates that bottleneck. This role is less about managing a backlog and more about becoming the deepest source of customer understanding on the team, translating real K–12 pain points into the structured context that AI agents and developers need to build the right thing, fast. This means spending less time in traditional Agile ceremonies and more time inside the build cycle, co-creating in real time alongside developers and AI agents, validating output as it is generated, and ensuring the team never loses the “why” behind what they are building. The right candidate brings deep empathy for K–12 customers, the precision to encode that understanding into markdown-based Vision Canvases, and the drive to prove that Human + AI + Dev produces more than the sum of their parts.

Requirements

A track record of building customer understanding into product decisions, whether through product management, customer success, support, or adjacent roles in SaaS or B2B environments.
Background in Agile or Scrum is a useful context, but we value your ability to work in a new model over your fluency in the old one.
Proficiency with markdown, or a strong willingness to master it quickly. In our FSAD model, POs “code” alongside developers using markdown as the programming language, directly translating design decisions into working code.
A CS degree is not required; what matters is the ability to encode customer intent precisely enough that it drives correct outcomes without rework.
Exceptional communication skills, with the ability to describe complex workflows, logic, and visual states clearly and concisely for both technical teammates and AI agents. Precision of language is a core job skill in this model, not a soft skill.
Strong analytical skills and experience with data-driven product design and decision-making.
Demonstrated comfort with ambiguity, fast-moving environments, and evolving processes.
Proficiency with product and project management tools such as Asana, Azure DevOps, Jira, Confluence, or Miro.
Genuine curiosity about AI tools and a demonstrated willingness to build new working habits around them, including hands-on experience with prompt engineering, AI-assisted workflows, and using structured markdown to drive development outcomes alongside engineering teammates.

Nice To Haves

Experience with workflow and service management platforms (ServiceNow, BMC, etc.) is preferred but not required.

Responsibilities

Develop deep, firsthand empathy for K–12 customer workflows, becoming the team’s ultimate source of truth on what users need, why they need it, and what “winning” looks like for them.
Transform customer pain points into high-fidelity Vision Canvases, structured markdown documents that provide the shared context AI agents and developers need to build the right thing without rework or misinterpretation.
Be present and active inside the build cycle, participating in real-time alongside developers and AI agents, validating code and UI/UX as it is generated rather than reviewing it days later in a handoff.
Participate in lightweight team cadences focused on outcomes and unblocking, not ceremony. Agile rituals serve the work; the work does not serve the rituals.
Design for the customer, not for the process, collaborating with designers and engineers to ensure every UX decision is grounded in real user workflows and validated quickly, not debated in planning docs.
Work closely with Customer Success to identify, triage, and resolve key product issues.
Support go-to-market initiatives and product launches with internal enablement and external communication.
Own and continuously sharpen the team’s shared context, ensuring every member of the pod, human and AI, understands the “why” behind every feature well enough to make good decisions independently.
Map new features and configure dashboards in Incident IQ’s third-party Product Usage Analytics Tool.
Serve as a product ambassador internally and externally, sharing knowledge, answering questions, and building trust.
Participate in collaborative AI-driven planning sessions where shared context is established before development begins, ensuring the whole team is aligned inside the same AI environment.
Author, iterate, and refine structured markdown files that define agent tasks, acceptance criteria, and workflow logic, functioning as the programming language through which product decisions are directly translated into working code.
Own the quality gate between AI-generated output and what ships, reviewing features, documentation, and test cases against the markdown context you authored to ensure product intent is fully preserved.
Author and own the structured context, in markdown, that both engineering teammates and AI agents work from, encoding product intent precisely enough that it drives correct outcomes without constant interpretation or handoff.
Partner with engineering and product leadership to help define and mature Incident IQ’s FSAD methodology as we progress toward a fully agentic development model.
Remain adaptable as tools, processes, and expectations evolve rapidly, bringing a growth mindset and willingness to experiment, learn, and iterate on how the team works.