AI Agent Full Stack Engineer

Company Description QodeShark focuses on proactively identifying and mitigating risks in software projects before they reach production environments. The organization evaluates security, performance, scalability, and technical debt issues to help teams deliver reliable and resilient systems. By embedding risk detection into the development lifecycle, QodeShark supports engineering teams in building high-quality, maintainable code. Team members work closely with product and engineering stakeholders to ensure that potential issues are surfaced early and addressed efficiently. Role Description The AI Agent Full Stack Engineer role is a full-time, hybrid position based in San Francisco, CA, with flexibility for some work-from-home days. In this role, the engineer designs, builds, and maintains full stack applications that power AI agents used to detect risks in codebases, including security vulnerabilities, performance bottlenecks, scalability issues, and technical debt. Day-to-day responsibilities include developing backend services and APIs, creating intuitive front-end interfaces, integrating AI/ML models, and optimizing systems for reliability and efficiency. The engineer collaborates with cross-functional teams to refine requirements, ship features, and improve existing tools based on user feedback and observed production behavior. The role also involves implementing automated tests, participating in code reviews, and contributing to architectural decisions for scalable AI-driven platforms. Qualifications Strong full stack engineering skills, including experience with modern backend frameworks, RESTful or GraphQL APIs, and frontend technologies such as React, Vue, or similar libraries.Experience integrating AI or machine learning models into production systems, including familiarity with model deployment, monitoring, and performance optimization.Background in software reliability and security, with knowledge of common vulnerabilities, performance profiling, scalability patterns, and strategies to reduce technical debt.Proficiency with cloud platforms (e.g., AWS, GCP, Azure), containerization, and CI/CD pipelines to support robust deployment and observability of full stack applications.Strong problem-solving and communication skills, with the ability to collaborate effectively in a hybrid environment and translate complex technical concepts into clear, actionable insights.Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience; prior experience in building developer tools or risk analysis systems is a plus.