Senior Software Engineer – Cortex AI

• Architect and scale orchestration engines for complex agentic workflows, with low-latency tool execution and robust state management
• Design high-performance RAG infrastructure, including vector database integration, search indexing, query processing, result ranking, semantic caching, and automated metadata extraction
• Develop automated infrastructure for large-scale golden set simulations, error analysis pipelines, and hill climbing experiments
• Collaborate with the modeling team to product ionize LLM capabilities as hardened, multi-tenant microservices with guardrails and observability
• Direct infrastructure strategy for model routing, prompt caching, and token optimization
• Build backend infrastructure powering Snowflake Intelligence, Cortex Agents, and Cortex Search
• Perform cross-layer debugging across services using logs and telemetry
• Evaluate customer problems and determine whether they represent bespoke issues or platform gaps worth addressing

• Bachelor’s degree in Computer Science or a related technical field
• 7+ years of experience building distributed systems, high-throughput APIs, or backend infrastructure for AI/ML products
• Deep proficiency in Go or Java and Python
• Strong understanding of database internals, distributed state management, and cloud-native architecture
• Experience with Kubernetes and Foundation DB or similar technologies
• Familiarity with vector indices, agent platforms, and scalable data pipelines
• Experience in a customer-facing technical role
• Product judgment to distinguish bespoke customer problems from platform gaps
• Cross-layer debugging using logs and telemetry
• Experience with eval frameworks for LLM/agent systems, including defining quality metrics and improving quality systematically
• Comfort with ambiguity on open-ended, externally-driven problems
• Bonus experience with query optimization, SQL engine internals, multi-tenant systems handling sensitive enterprise data, and large-scale search infrastructure

Demonstrates expertise in architecting and scaling orchestration engines and backend infrastructure for AI/ML products, with a strong focus on distributed systems, cloud-native architecture, and cross-layer debugging. Proficient in developing high-performance RAG infrastructure and automated simulations while collaborating effectively with technical teams.

• Distributed Systems Development
• Go, Java, And Python Proficiency
• Kubernetes And Foundation DB Experience
• Cross-Layer Debugging Using Logs And Telemetry
• LLM/Agent Systems Evaluation Frameworks

• Distributed Systems
• High-Throughput APIs
• Backend Infrastructure
• Database Internals
• Cloud-Native Architecture
• Query Optimization
• SQL Engine Internals
• Error Analysis Pipelines
• Automated Metadata Extraction
• Scalable Data Pipelines

• Product Judgment
• Comfort With Ambiguity
• Customer-Facing Technical Role

• Bachelor’s Degree In Computer Science

• AI/ML Products
• Agent Platforms
• Multi-Tenant Systems
• Large-Scale Search Infrastructure

• Kubernetes
• Foundation DB
• Vector Database
• Telemetry Tools
• Logs Analysis