Member of Technical Staff, Full Stack, LLM Applications

**The Role**

We seek experienced Full Stack Software Engineers to build the applications and infrastructure that bring our diffusion LLMs to users. You will design and develop both frontend interfaces and backend services — creating intuitive experiences and robust APIs capable of serving at scale. You'll work closely with ML engineers and researchers to bridge the gap between complex AI models and user-friendly products.

**Key Responsibilities**

• Design and develop scalable web applications and APIs for our models, building both frontend interfaces and backend services.
• Build systems for internal experimentation and monitoring that provide observability across our entire tech stack.
• Develop RESTful APIs to expose model capabilities to external applications.
• Implement authentication, authorization, and security best practices for enterprise deployments.
• Collaborate with ML engineers to integrate model serving infrastructure with the application layer.
• Design infrastructure as code, deployment automation, and CI/CD pipelines.

**Qualifications**

• BS/MS/PhD in Computer Science, Machine Learning, or a related field (or equivalent experience).
• 5+ years of experience building production web applications.
• Strong proficiency in modern JavaScript/TypeScript and Python.
• Experience with frontend frameworks (e.g., React) and state management solutions.
• Solid understanding of backend development, including API design, database management, and microservices architecture.
• Experience with SQL and NoSQL databases (e.g., Neon).
• Familiarity with Kubernetes, CI/CD pipelines, and cloud infra (AWS and/or Azure).
• Experience with version control (Git) and collaborative development workflows.
• Strong problem-solving skills and the ability to work in a fast-paced startup environment.

**Preferred Skills**

• Experience building applications that integrate with AI/ML systems.
• Knowledge of streaming architectures and real-time data processing.
• Experience with monitoring and observability tools (Prometheus, Grafana).
• Understanding of ML concepts and experience with ML frameworks (PyTorch, TensorFlow).
• Experience with infrastructure as code tools (Terraform).
• Experience with testing frameworks and test-driven development.
• Experience with UI/UX design and Framer.