Senior Software Engineer - Cortex AI - FDE

Role Summary

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.

The Cortex Apps team is building the future of AI for enterprise data. This role focuses on the backend infrastructure that powers our flagship products like Snowflake Intelligence, Cortex Agents and Search making agentic AI fast, reliable, scalable and secure at the enterprise level.

You won’t just be using AI tools; you will be building the high-performance systems that orchestrate them. You’ll own and influence the architecture for agent execution environments, high-throughput context retrieval, or the ecosystem that allows our customers to iterate and launch agents in production.

(BONUS) EXPERIENCE WITH

• Query optimization and SQL engine internals.
• Designing multi-tenant systems that handle sensitive enterprise data at scale.
• Developing search infrastructure for large-scale applications.
• Direct experience with any of the subsystems outlined above.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.

Responsibilities

WHAT YOU WILL DO IN THIS ROLE

• 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.
• How do you want to make your impact?
• For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com http://careers.snowflake.com

Requirements

• Education: Bachelor’s degree in Computer Science or a related technical field.
• Experience: 7+ years of experience building distributed systems, high-throughput APIs, or backend infrastructure for AI/ML products.
• Technical Stack: Deep proficiency in Go or Java (for systems) and Python (for AI orchestration).
• Systems Thinking: Strong understanding of database internals, distributed state management, and cloud-native architecture (Kubernetes, FoundationDB, etc.).
• Domain Expertise: Familiarity with the "plumbing" of AI: vector indices, agent platforms, and building scalable data pipelines.
• Experience in a customer-facing technical role — you have explained a hard failure to a frustrated external audience and been believed, you can produce both the internal analysis and the customer-safe version.
• Product instinct — you can judge whether one customer's problem is bespoke or a platform gap worth fixing for everyone. This is the core judgment call.
• Cross-layer debugging — tracing a request across services and root-causing in unfamiliar code from logs and telemetry, not guesswork.
• Eval frameworks for LLM/agent systems — defining quality metrics and using evals to improve quality systematically over time.
• Comfort with ambiguity on open-ended, externally-driven problems.

About the Company

ABOUT THE AI PRODUCTS TEAM

The AI Products team is part of the broader Marketplace & Collaboration organization and is focused on bringing AI products on top of Snowflake’s data and application platform to help customers discover, share, monetize, and act on data assets & applications more easily.

This team is building the connective tissue of the agentic enterprise: the infrastructure and product surfaces that allow Snowflake customers to seamlessly share datasets, semantic views, and applications, and make them discoverable and executable through Cortex Code, CoWork, and other agentic harnesses.

Our strategy is centered on evolving Snowflake Marketplace for the AI era, including packaging data and intelligence into ready-to-use agentic experiences, and enabling governed access patterns that let AI systems safely operate on enterprise data and applications.

AS A STAFF SOFTWARE ENGINEER ON AI PRODUCTS, YOU WILL

WHY JOIN THIS TEAM

This is a chance to shape how Snowflake customers expose data and applications to AI systems in a secure, governed, and highly usable way. The work sits at the intersection of platform engineering, product innovation, and AI transformation, and it directly influences how the Data Cloud evolves for the next generation of customers and builders.