Чем предстоит заниматься
Architect Agentic Runtimes: Build and scale the orchestration engines that execute complex agentic workflows, ensuring low-latency tool execution and robust state management
Scale Context Engineering Infra: Design high-performance systems for RAG (Retrieval-Augmented Generation), including vector database integration, scalable and efficient search indexing, query processing, and result ranking, semantic caching, and automated metadata extraction
Build the "Evals Engine": Develop the automated infrastructure required to run massive-scale golden set simulations, error analysis pipelines, and "hillclimbing" experiments
Productionize AI Workflows: Collaborate with the modeling team to take raw LLM capabilities and turn them into hardened, multi-tenant microservices with strict guardrails and observability
Optimize Performance & Cost: Direct the infra strategy for model routing, prompt caching, and token optimization to ensure Snowflake’s AI features are the most efficient in the industry