Full-Stack Engineer (Agentic Development Platform)

About this role

Position Summary We are seeking a Full-Stack Developer to build and evolve an AI-powered software development environment using Kiro (or similar agentic AI platforms). In this role you will be a hands-on engineer who implements the platform’s core components, reusable frameworks, and AI-assisted workflows, enabling Product, Design, Engineering, and Business teams to collaboratively build applications faster and with consistent quality.

You will work within the architectural direction set by the platform’s architects and contribute to technical decisions, while owning the delivery of features end to end. Key Responsibilities Agentic Development Platform Build and maintain components of an enterprise-grade agentic development environment using Kiro or similar platforms. Implement multi-agent workflows that support requirements generation, design, code generation, testing, and documentation.

Contribute to scalable development patterns and reusable frameworks for application delivery. Rapid Prototyping & AI-Assisted Development Develop MVPs and proofs of concept, working closely with Product and Design partners. Turn business requirements and natural language inputs into user stories, technical designs, UI prototypes, and working applications. Iterate on and refine concepts through AI-assisted development cycles, gathering stakeholder feedback along the way.

Full-Stack Engineering & Reusability Build and maintain reusable assets, including: Application templates and starter kits Angular component libraries NestJS/Node.js service frameworks AI agent workflows and prompt libraries Apply and promote consistent architecture and coding standards across teams. Write clean, well-tested, and well-documented code, and participate actively in code reviews. AI Agent Integration Implement and tune workflows involving requirements, design, code generation, testing, and documentation agents.

Integrate LLM-based tools into the software delivery lifecycle, including CI/CD pipelines. Evaluate AI-generated output for correctness, security, and maintainability, and improve prompts and workflows based on results. Adoption & Quality Support adoption of AI-native development practices across Product, Design, and Engineering teams. Help implement governance, security, quality controls, and validation processes for AI-generated artifacts.