Staff AI Engineer

Key details

• Shape the technical direction of Research Flow and AI systems across products
• Lead architectural decisions across AI-assisted study design, adaptive conversations, and research synthesis
• Design and build generative AI applications using large language models, RAG, vector search, tool use, and agentic systems
• Guide the architecture of machine learning services and workflows using Python, Docker, Kubernetes, and AWS
• Design reliable pipelines for batch and real-time processing using technologies such as Kafka and Airflow
• Establish patterns for retrieval, vector search, model orchestration, and working with structured and unstructured data
• Improve experiment management, model versions, registries, and deployments using tools such as MLflow
• Define evaluation strategies and release criteria for generative AI applications
• Guide the development of automated benchmarks covering accuracy, relevance, reliability, fairness, latency, and cost
• Lead improvements to retrieval quality, including chunking, embeddings, context selection, and reranking
• Build reusable services and APIs that help product teams deliver AI capabilities consistently
• Lead initiatives requiring coordination across Product, Engineering, Data Science, and Data Engineering
• Company mission
• Information not specified