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.