Why This Job is Featured on The SaaS Jobs
This role sits at a core intersection in modern SaaS: enterprise cloud data platforms and the emerging layer of agentic AI applications. Working on Cortex AI Infrastructure means focusing on the systems that make AI features usable in production, including orchestration, retrieval and search, evaluation pipelines, and multi-tenant service hardening. In the SaaS ecosystem, that combination is increasingly central as vendors move from demos to dependable AI capabilities embedded in products.
From a career standpoint, the work maps to durable SaaS engineering themes: distributed systems design, reliability and observability, performance tuning, and platform thinking. Experience building context engineering infrastructure such as RAG components, semantic caching, and scalable indexing translates across many SaaS categories now shipping AI powered functionality. The emphasis on turning model behavior into governed services also develops instincts that matter in enterprise SaaS, where correctness, security boundaries, and repeatable evaluation are part of product quality.
The position is best suited to engineers who prefer foundational backend work over UI, and who like owning ambiguous infrastructure problems with measurable latency and throughput outcomes. It aligns with professionals who want to deepen systems expertise while staying close to how SaaS products operationalize AI at scale.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
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.
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers who are energized by the opportunity to reinvent how they work. The Cortex Apps team is building the future of AI for enterprise data, and this role focuses on the backend infrastructure that powers our flagship products like Snowflake Intelligence, Cortex
Agents, and Search. You won't just be using AI tools; you will be building the high-performance systems that orchestrate them, making agentic AI fast, reliable, scalable, and secure at the enterprise level.
What you will do in this role:
Build Agentic Runtimes: Help build and scale the orchestration engines that execute complex agentic workflows, ensuring low-latency tool execution and robust state management.
Scale Context Engineering Infra: Develop and design high-performance systems for RAG (Retrieval-Augmented Generation), including vector database integration, scalable search indexing, query processing, and semantic caching.
Develop the "Evals Engine": Build the automated infrastructure required to run massive-scale golden set simulations, error analysis pipelines, and 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: Implement system optimizations for model routing, prompt caching, and token optimization to ensure maximum efficiency.
Requirements:
Education: Bachelor's degree in Computer Science or a related technical field; Masters or PhD preferred.
Experience: 4+ years of industry experience designing, building, and supporting distributed systems, high-throughput APIs, machine learning platforms, or data-intensive systems.
Technical Stack: Deep proficiency in Python (for AI orchestration) and strong experience with Go or Java (for systems). Familiarity with C++ is a plus.
Systems Thinking: Strong understanding of database internals, distributed state management, and cloud-native architecture (e.g., Kubernetes, FoundationDB). Experience setting up and maintaining CI/CD pipelines is a plus.
Domain Expertise: Familiarity with the "plumbing" of AI, such as vector indices, agent platforms, building scalable data pipelines, and working with frameworks like PyTorch, TensorFlow, or XGBoost.
Mindset: A growth mindset and excitement about breaking the status quo by seeking innovative solutions.
(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
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
