Teams at Sentient Foundation

Design and operate fault-tolerant, performance-critical backend infrastructure across AWS and GCP. Build serverless services, REST and WebSocket APIs, secure cloud deployments, and scalable AI workflows including fine-tuning and inference pipelines. Develop custom AI agent and multi-agent frameworks, manage containerized services, follow release processes, and document systems. The role requires strong Python expertise, extensive cloud and Kubernetes experience, infrastructure-as-code knowledge, and familiarity with generative AI and LLMs.

Build end-to-end machine learning systems spanning research reproduction, model evaluation, inference infrastructure, backend services, and product interfaces. Design rigorous experiments, evaluation datasets, and verification workflows; analyze model internals; investigate provenance and evasion; and convert findings into reliable production systems with APIs, background jobs, observability, testing, documentation, and user-facing React/TypeScript experiences.