AI-Native Technical Project Manager Software Architect

About the Company
The AI-Native Technical Project Manager & Software Architect is responsible for turning business ideas and product visions into fully developed software, websites, and technical systems using AI-driven development tools. This role serves as the architect and general contractor for multiple projects at once. It owns the technical planning, organizes the development process, directs AI coding tools, reviews their output, and manages each project from initial concept through deployment. The role requires a combination of project management, software engineering, full-stack development knowledge, technical architecture, and advanced use of artificial intelligence.
About the Role

This role is responsible for managing multiple software and website projects simultaneously, ensuring that the founder’s vision is translated into clear product requirements and technical plans.

Responsibilities
Understand the founder’s vision, goals, and intended user experience for each project.Translate broad ideas into clear product requirements, technical plans, system architecture, and development tasks.Manage multiple software and website projects simultaneously.Prioritize tasks, track progress, manage dependencies, and determine the next steps for each project.Break complex projects into smaller assignments that can be completed by AI coding tools and agents.Select and manage the appropriate AI model, coding agent, or development tool for each task.Work efficiently with tools such as ChatGPT, Claude, GitHub, AI coding agents, and other AI development platforms.Write detailed and effective prompts that provide AI tools with the correct context, requirements, documentation, and technical constraints.Coordinate multiple AI tools as specialized development resources while maintaining control over the complete project.Manage token usage, context windows, documentation, and AI conversations to reduce unnecessary costs, repeated work, and lost context.Review, test, and validate AI-generated code and technical decisions.Identify incorrect, incomplete, insecure, or unnecessarily complicated solutions produced by AI.Debug technical problems and make corrections when AI-generated work does not meet the project requirements.Oversee frontend development, backend development, databases, APIs, authentication, integrations, infrastructure, and deployment.Maintain organized project documentation so that work can continue efficiently across different tools, sessions, and projects.Take responsibility for the technical quality and successful completion of each project.

Qualifications
Strong understanding of software engineering and full-stack development.Ability to read, understand, review, debug, and improve code, even when most of the code is generated by AI.Understanding of frontend and backend systems, databases, APIs, authentication, and third-party integrations.Experience with application architecture, infrastructure planning, cloud hosting, and production deployments.Strong knowledge of GitHub, version control, branches, pull requests, and code reviews.Deep understanding of how AI models and AI coding tools work, including their strengths, limitations, and common failure points.Advanced ability to prompt AI tools, manage context, structure instructions, and choose the correct model or agent for each task.Ability to manage several technical projects without losing track of their architecture, requirements, current status, or next steps.

Required Skills

Strong understanding of software engineering and full-stack development.Ability to read, understand, review, debug, and improve code, even when most of the code is generated by AI.Understanding of frontend and backend systems, databases, APIs, authentication, and third-party integrations.Experience with application architecture, infrastructure planning, cloud hosting, and production deployments.Strong knowledge of GitHub, version control, branches, pull requests, and code reviews.Deep understanding of how AI models and AI coding tools work, including their strengths, limitations, and common failure points.Advanced ability to prompt AI tools, manage context, structure instructions, and choose the correct model or agent for each task.Ability to manage several technical projects without losing track of their architecture, requirements, current status, or next steps.