Senior AI Engineer, Enterprise

Posted 14 Days Ago
Be an Early Applicant
Menlo Park, CA, USA
In-Office
156K-224K Annually
Senior level
Artificial Intelligence • Big Data • Cloud • Machine Learning • Software • Database • Analytics
Let's build a world where data and AI turn possibilities into reality.
The Role
Build scalable backend services, distributed systems, APIs, and platform infrastructure for production AI and agentic applications. Develop reusable agent frameworks, evaluation pipelines, SDKs, and Python libraries while improving CI/CD, testing, observability, security, reliability, and cost efficiency. Use Snowflake’s AI ecosystem to deliver intelligent internal products, collaborate with cross-functional stakeholders, and establish engineering best practices for enterprise AI systems.
Summary Generated by Built In

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.

ABOUT THE TEAM

The GTM AI Engineering team is part of Snowflake's Data Analytics & AI organization and builds the internal AI platform and intelligent applications that power Snowflake's Go-To-Market organization. We develop production-grade AI systems used daily by thousands of employees across Sales, Solution Engineering and Marketing.

As a Senior AI Engineer, you will build the backend services, platform infrastructure, and AI capabilities that power next-generation agentic applications. You will work at the intersection of distributed systems, backend engineering, applied AI, and internal product development, designing scalable, reliable, and secure systems that enable intelligent experiences with direct business impact.

This role offers the opportunity to shape a rapidly growing internal AI platform, establish engineering best practices, and build AI products that directly accelerate Snowflake's growth.

IN THIS ROLE, YOU WILL:
  • Design and build scalable backend services and distributed systems that power production AI and agentic applications.

  • Develop APIs, orchestration services, and platform capabilities for internal AI products.

  • Build reusable AI platform components, including agent frameworks, evaluation pipelines, developer SDKs, templates, and shared Python libraries.

  • Evolve our engineering platform through modern CI/CD pipelines, automated testing, deployment tooling, and developer experience improvements.

  • Optimize AI infrastructure and backend services for performance, scalability, reliability, security, and cost efficiency.

  • Leverage Snowflake Cortex, Snowpark, and the broader Snowflake AI ecosystem to build intelligent data applications.

  • Establish engineering best practices around testing, observability, monitoring, evaluation, and production readiness for AI systems.

  • Collaborate closely with product managers, data engineers, designers, and GTM stakeholders to deliver high-impact AI solutions.

  • Stay current with advances in AI engineering and help drive adoption of modern technologies, frameworks, and development practices across the team.

WE WOULD LOVE TO HEAR FROM YOU IF YOU HAVE:Required Qualifications
  • 5+ years of professional software engineering experience with a Bachelor's degree (or higher) in Computer Science, Software Engineering, or a related technical field.

  • Strong proficiency in Python (3.11+) with experience writing production-quality, well-tested, maintainable code using modern Python practices.

  • Experience building RESTful APIs and backend services using FastAPI or similar frameworks.

  • Experience designing and operating distributed systems and microservice architectures.

  • Strong understanding of software engineering best practices, including testing, CI/CD, code quality, observability, and production operations.

  • Experience with containerization technologies such as Docker.

  • Hands-on experience building production AI applications using large language models.

  • Experience with prompt engineering, tool calling, structured outputs, and LLM orchestration frameworks.

  • Strong problem-solving skills, excellent communication, and the ability to work effectively in a fast-paced, collaborative environment.

Preferred Qualifications
  • Experience with the Snowflake platform, including Snowpark, Cortex AI, Snowpark Container Services, Snowflake Connector, and Snowflake CLI.

  • Experience building agentic applications using frameworks such as LangGraph or similar multi-agent orchestration frameworks.

  • Experience with AI evaluation, monitoring, guardrails, and observability frameworks.

  • Familiarity with model serving, inference optimization, and AI infrastructure.

  • Experience working with large-scale data platforms, ETL pipelines, and modern data engineering workflows.

  • Experience building full-stack AI applications using Streamlit, React, or similar frameworks.

  • Experience with Python data libraries such as pandas and NumPy.

  • Familiarity with modern AI development tools such as Cursor, Claude Code, Cortex Code, or similar AI-assisted development environments.

  • Experience working with cloud-native infrastructure and Kubernetes is a plus.

WHY JOIN OUR TEAM?

Joining the GTM AI Engineering team means building AI products that have a direct and measurable impact on Snowflake's business. You'll help define the architecture of our internal AI platform while developing intelligent applications used every day by thousands of employees across our global Go-To-Market organization.

This is a unique opportunity to combine backend engineering, distributed systems, and applied AI to solve real business problems at scale. You'll work alongside world-class engineers and product leaders while helping shape how AI transforms the way Snowflake operates internally.

If you're passionate about building production-grade AI systems, enjoy solving complex engineering challenges, and want to help define the future of enterprise AI, we'd love to hear from you.

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

Skills Required

  • 5+ years of professional software engineering experience
  • Bachelor’s degree or higher in Computer Science, Software Engineering, or a related technical field
  • Strong proficiency in Python 3.11+ and production-quality software development
  • Experience building RESTful APIs and backend services using FastAPI or similar frameworks
  • Experience designing and operating distributed systems and microservice architectures
  • Understanding of software engineering practices including testing, CI/CD, code quality, observability, and production operations
  • Experience with containerization technologies such as Docker
  • Hands-on experience building production AI applications using large language models
  • Experience with prompt engineering, tool calling, structured outputs, and LLM orchestration frameworks
  • Strong problem-solving, communication, and collaboration skills
  • Experience with Snowflake, Snowpark, Cortex AI, Snowpark Container Services, Snowflake Connector, or Snowflake CLI
  • Experience building agentic applications with LangGraph or similar multi-agent orchestration frameworks
  • Experience with AI evaluation, monitoring, guardrails, and observability frameworks
  • Familiarity with model serving, inference optimization, and AI infrastructure
  • Experience with large-scale data platforms, ETL pipelines, and modern data engineering workflows
  • Experience building full-stack AI applications using Streamlit, React, or similar frameworks
  • Experience with pandas and NumPy
  • Familiarity with AI-assisted development tools such as Cursor, Claude Code, or Cortex Code
  • Experience with cloud-native infrastructure and Kubernetes

Snowflake Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Snowflake and has not been reviewed or approved by Snowflake.

  • Fair & Transparent Compensation — Pay is often characterized as top‑of‑market across multiple roles. The company also points to a Fair Pay Workplace certification, signaling externally reviewed pay‑equity practices.
  • Equity Value & Accessibility — Equity is a meaningful part of total compensation, with new‑hire grants, refresh potential, and a discounted ESPP with a favorable lookback. Feedback suggests this ownership component materially boosts perceived total rewards.
  • Leave & Time Off Breadth — Parental leave is described as up to 26 weeks paid in the U.S., paired with flexible or generous PTO and multiple leave types. Family‑building benefits and a dedicated parental‑leave hub further expand support.

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The Company
HQ: Bozeman, MT
9,023 Employees
Year Founded: 2012

What We Do

Snowflake powers the end-to-end data lifecycle – from ingesting and processing data to analyzing and modeling it, to building and sharing data and AI applications – helping engineers, analysts, and leaders innovate faster and achieve more with their data. We're on a mission to empower every enterprise to achieve its full potential through data and AI.

Why Work With Us

Snowflake is where data does more, and so do you. More innovating, more growing, and more collaborating. Here, you’ll find the sweet spot between building big and moving fast, in technology and your career.

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