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.