Role Summary
The Product Manager will define and drive product capabilities for a stealth AI platform focused on large-data analysis, prediction, model-driven decision making and operational improvement. The role requires someone who can understand complex technical systems and translate them into usable product requirements, priorities and delivery plans.
This is not a purely business-facing product role. The person must be comfortable working with engineers, data scientists, designers and customer stakeholders to define workflows, acceptance criteria, metrics and phased releases. The product will span multiple segments, so the PM must be able to generalize customer problems into reusable platform capabilities.
What You Will Do
- Define product requirements for data ingestion, analytics, AI decision support, model outputs, dashboards, workflows, user roles and automation features.
- Translate customer and business needs into clear user stories, acceptance criteria, milestones and product priorities.
- Work closely with engineering, design, data science and leadership to balance speed, quality, technical feasibility and customer value.
- Create product documentation, workflow diagrams, release notes, demo scripts and internal enablement materials.
- Prioritize the roadmap based on business impact, technical dependencies, customer urgency and platform reuse.
- Define success metrics for product capabilities, including adoption, workflow completion, decision quality, user satisfaction and measurable operational improvement.
- Lead discovery discussions and synthesize ambiguous input into structured product decisions.
- Review product builds, test workflows and ensure delivered features meet the intended user need.
- Help convert segment-specific requirements into generic platform capabilities that can be reused across future projects.
- Maintain a practical backlog that helps a startup team move quickly without losing clarity.
Requirements and Skills
- 5+ years of product management experience for technical software products, preferably data, AI, analytics, automation or enterprise platforms.
- Strong ability to understand complex technical concepts and translate them into clear product requirements.
- Experience working directly with engineers, data scientists, designers and customer stakeholders.
- Strong written communication skills, including user stories, PRDs, workflow documentation and concise executive summaries.
- Ability to prioritize objectively when requirements, schedules and technical dependencies are changing.
- Strong product judgment around usability, customer value, MVP scope and staged delivery.
- Comfortable with data products, dashboards, APIs, model outputs and workflow automation concepts.
- Experience defining acceptance criteria and validating features before release.
- Ability to operate independently in a startup environment without relying on heavy corporate product process.
Preferred Background
- Experience with large-scale analytics platforms, AI/ML products, enterprise software, workflow systems or business optimization tools.
- Experience with telecom, energy, IoT, operations software or analytics platforms is a plus.
- Familiarity with tools such as Jira, Linear, Notion, Confluence, Figma, Miro, Postman or analytics tools.
- Experience working with early customers where product requirements are still evolving.
Startup Environment
This is a startup environment for people who want meaningful responsibility rather than narrowly defined corporate roles. Team members should expect exposure to multiple parts of the business, including product design, engineering decisions, customer problem solving, implementation planning and operational execution. The team will be small, highly technical and organized around talented builders who can work directly with one another without unnecessary layers of hierarchy. We expect people to use modern development tools aggressively, including coding assistants, automation, test tools, model tooling and sufficient token budgets where they improve speed and quality. The working style is flexible, but the expectations are high: clear ownership, written thinking, disciplined execution, frequent communication, clean handoffs and the ability to make progress without waiting for a complete corporate structure.
What Success Looks Like
- Engineering teams receive clear, actionable requirements with well-defined priorities and acceptance criteria.
- Product capabilities become reusable across multiple customer segments instead of one-off custom work.
- Customer needs are captured accurately and turned into phased product releases.