Jobs / United States / Snowflake INC

Snowflake INC

Senior AI Engineer, Enterprise

US-CA-Menlo Park Posted 15 days ago

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Skills this job asks for

SnowflakePythonCI/CDREST APIsDockerLLMs

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 428 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Snowflake INC paid sponsored hires in similar roles148 certified filings for “Software Engineer” (Software Developers) in CA: $160k–$214k, median $188k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 428 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Snowflake INC paid sponsored hires in similar roles
148 certified filings for “Software Engineer” (Software Developers) in CA: $160k–$214k, median $188k. Most were filed at wage level II (41%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

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

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