We are seeking a Senior AI Engineer with strong expertise in ReactJS and Python to join our team and help build, debug, and scale intelligent applications powered by LLMs and agent-based architectures. The ideal candidate combines deep backend engineering skills with a sharp eye for frontend quality and thrives on tracing complex issues across the full stack - from UI rendering to agent reasoning failures. Responsibilities Design and build async endpoints, background tasks, and streaming responses using Python and FastAPI Develop and maintain agent-based systems, including prompt design, tool-calling, and RAG pipelines Diagnose and resolve LLM failure modes such as hallucination, context contamination, and non-deterministic output Tune retrieval quality through chunking strategies, embeddings, and vector search optimization Build and fix production-grade React UIs, including layout, responsive behavior, and streaming state management Identify and resolve concurrency issues, including shared mutable state and callback bleed under concurrent requests Operate within Docker and Kubernetes environments, including deployment and pod/log debugging Write and maintain test coverage using pytest and vitest, including mocks and fixtures Trace symptoms to root causes across frontend, backend, and agent layers to ensure system reliability Requirements 5+ years of experience with Python, FastAPI, and asynchronous programming patterns Proficiency in agent frameworks such as pydantic-ai, LangGraph, or LangChain, with hands-on experience in prompt engineering and tool-calling Expertise in RAG systems, including chunking, embeddings, and vector search tools such as Qdrant or pgvector Skills in React (hooks) and CSS, with the ability to build and troubleshoot complex, responsive UIs Understanding of concurrency and state management, with experience implementing request-scoped state, locks, and thread-safety Familiarity with Docker and Kubernetes, including container management and deployment debugging Background in testing practices using pytest and vitest, with consistent use of mocks and fixtures Strong debugging skills with the ability to trace issues across frontend, backend, and agent layers Nice to have Experience with AWS Bedrock or other model gateway platforms beyond OpenAI Familiarity with Langfuse or other LLM observability tooling Knowledge of python-pptx or document generation tools for PowerPoint and PDF outputs Background in regulated industries such as pharma or life sciences, including familiarity with FDA PMA/510(k) and IVDR terminology Skills in Helm chart authoring and CI/CD pipelines using GitHub Actions Design sensibility for building premium, non-generic user interfaces Experience integrating SSO/OAuth solutions such as Azure AD or MSAL Familiarity with vector DB operations, including Qdrant collection management and embedding pipeline maintenance Understanding of prompt-eval or LLM-testing frameworks for measuring answer quality over time