G63 - Full Stack Engineer

Responsibilities • Lead the end-to-end technical implementation and delivery of Litmus & Sentinel, serving as a subject matter expert in full-stack architecture while ensuring the responsible and ethical use of AI technologies. • Drive technical discussions and integration efforts with cross-functional teams to successfully integrate Litmus & Sentinel into products and platforms. • Take ownership of deployment pipelines, ensuring high system availability, scalability, and seamless integration. • Design and implement scalable, resilient, and high-performing frontend and backend architectures using modern technologies and engineering best practices. • Establish and uphold high engineering standards through code reviews, performance optimization, and mentorship of engineering team members. • Translate complex technical and ethical requirements from product managers, data scientists, and stakeholders into actionable technical roadmaps and robust solutions. • Research and apply industry trends, AI ethics, and governance best practices to drive architectural improvements and strategic enhancements for AI guardrail products. Qualifications Technical Requirements • Minimum 3 years of hands-on experience as a Full-Stack Software Engineer, building and maintaining scalable, production-grade applications. • Strong expertise in developing responsive, dashboard-style frontends using modern frameworks such as Next.js (TypeScript). • Strong experience designing and building scalable backend APIs using frameworks such as NestJS (TypeScript) and FastAPI (Python). • Proficiency in cloud-native application development, preferably on AWS. • Experience with CI/CD pipelines, containerization technologies (e.g., Docker, Kubernetes), and deployment/monitoring practices. • Experience building applications leveraging Generative AI or Large Language Models (LLMs) is a strong advantage. Professional Attributes • Proven ability to write clean, efficient, maintainable, and well-tested code to solve complex engineering challenges. • Strong critical thinking and problem-solving skills, with the ability to anticipate edge cases and design fault-tolerant systems. • Excellent communication and leadership skills, with the ability to explain architectural decisions and provide technical guidance across teams. • Experience using AI-assisted development tools to improve engineering productivity and workflows. Cultural & Mission Alignment • Strong interest in data science, artificial intelligence, and machine learning, particularly in the areas of AI ethics and governance. • Proactive and ownership-driven mindset with the ability to independently drive projects to completion.