AI Product Engineer - Internal Apps

The Product Engineer is responsible for building practical internal applications that help KnowledgeCity teams work faster, make better decisions, and reduce manual work. This is an AI-first product-building role rather than a traditional software engineering position. The ideal candidate is highly comfortable with development concepts and is exceptionally strong at using AI-assisted development tools to turn business requirements into functional applications for reporting, analytics, operations, workflow management, and task execution. This role works directly with teams across the company to understand problems, prototype solutions quickly, connect systems and data, and continuously improve applications based on real-world usage.

• →Build and maintain internal applications, dashboards, utilities, and workflow tools using AI-assisted development methods.
• →Work directly with stakeholders across departments to understand business processes, pain points, requirements, and desired outcomes, then translate them into practical application solutions.
• →Rapidly prototype, test, and iterate on internal products, moving from concept to a usable production application with minimal unnecessary complexity.
• →Develop reporting and analytics applications that consolidate data, surface key metrics, and give teams clearer visibility into performance and operations.
• →Build operational tools for approvals, task execution, data entry, status tracking, workflow management, and other repeatable cross-functional processes.
• →Connect applications to APIs, databases, AI models, and business systems, including handling authentication, data flows, webhooks, and system integrations as needed.
• →Design and refine AI-powered features, prompts, workflows, and system logic, and validate outputs for reliability, accuracy, and usability.
• →Test, troubleshoot, and improve applications after launch, including resolving bugs, monitoring usage, managing versions, and maintaining dependable user experiences.
• →Document applications, workflows, data sources, permissions, and operating procedures, and support users with adoption and training when needed.

• Demonstrated experience building functional applications, internal tools, automations, or digital workflows using AI coding tools, low-code/no-code platforms, traditional development, or a combination of these approaches.
• Exceptional ability to use AI-assisted development tools to plan, build, debug, and improve applications efficiently.
• Strong understanding of core application development concepts, including front-end and back-end logic, APIs, databases, data models, authentication, webhooks, deployment, and version control.
• Ability to read, modify, test, and troubleshoot AI-generated code even without a traditional software engineering background.
• Strong product thinking and process-mapping skills, with the ability to turn ambiguous operational problems into clear workflows and usable tools.
• Comfort working with business data and analytics, including structuring data, validating outputs, and creating useful reporting experiences.
• Experience integrating SaaS platforms and internal systems through APIs, automation tools, or direct application connections.
• Strong attention to quality, permissions, security, and appropriate handling of company and customer data when building internal applications.
• Strong communication, documentation, prioritization, and ownership skills, with the ability to manage multiple internal application requests and drive them through completion.