• The AI‑Enabled Full Stack Developer plays a critical role in designing, developing, and maintaining scalable, secure, and high‑quality applications • Responsible for end‑to‑end front‑end and back‑end development and for integrating AI‑driven capabilities into enterprise applications • Collaborates closely with cross‑functional teams to deliver innovative, maintainable, and performant solutions that align with business objectives • Design and develop responsive, user‑friendly web interfaces using HTML, CSS, JavaScript, and modern frameworks such as React or Angular • Build and maintain server‑side logic, APIs, and services using technologies such as Node.js, Express, and supporting frameworks • Integrate AI services and capabilities into applications, including LLM APIs, AI agents, intelligent search, summarization, recommendations, and workflow automation • Prototype quickly, then harden solutions for production with monitoring, logging, evaluation, and performance optimization • Leverage AI coding tools (e.g., copilots, code generation, refactoring, and test generation tools) to improve development speed, code quality, and maintainability • Implement guardrails for AI systems including prompt safety, data protection, hallucination mitigation, access control, and output validation • Seamlessly integrate front‑end, back‑end, AI services, and third‑party systems to deliver cohesive and performant user experiences • Write, execute, and maintain automated tests, including unit, integration, and AI‑assisted test generation, to ensure application stability and reliability • Maintain and enhance existing applications, optimizing performance, security, and scalability while incorporating AI‑driven improvements where appropriate • Apply secure coding practices and ensure compliance with data privacy and security standards • Work closely with product owners, designers, architects, and other developers to deliver solutions aligned with business requirements and technical standards • Produce clear documentation for codebases, APIs, AI integrations, and development processes to support maintainability and knowledge sharing • Stay current with emerging AI technologies, frameworks, and development practices, and recommend practical adoption opportunities to enhance the development lifecycle • Mentor and upskill existing developers on AI concepts, patterns, and best practices.