Staff Software Engineer, Cortex AI Search Infrastructure
Snowflake is hiring a Staff Software Engineer, Cortex AI Search Infrastructure for a remote role open to applicants in United States. It pays $236k-$339k a year and Level rates it ; you can apply on Snowflake.
Level's read on this job
- Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
- The listed pay starts 40% above the typical software engineer posting on Level.
- The posting lists this role as remote.
- Tools and skills the posting cites include Vector Database, RAG and LLM.
- Level lists 353 other open roles at Snowflake.
AI in this role
Architect high-performance search infrastructure, retrieval engines, and agentic runtimes for Snowflake Cortex AI.
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 team is building the future of AI for enterprise data. This role focuses on the Search infrastructure that powers our flagship products like CoWork, Cortex Code & Cortex Agents fast, reliable, scalable and secure at the enterprise level.
You will be building high-performance retrieval engines (leveraging vector search, hybrid search, and semantic indexing) that power Snowflake Cortex. This involves optimizing how billions of rows of data are indexed and retrieved in milliseconds.
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.
Requirements:
Education: Bachelor’s degree in Computer Science or a related technical field.
Experience: 9 + 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.
(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.
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee’s duty to keep customer information secure and confidential.
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.
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
How we rate this
Staff Software Engineer, Cortex AI Search Infrastructure at Snowflake rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- This job starts at
- $236k
- Typical software engineer job
- $168k
This posting starts 40% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where search infrastructure was part of your work. What did you do?
- Tell me about a project where ai infrastructure was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, Distributed Systems, Search Infrastructure, and AI Infrastructure. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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