AI Engineer Jobs at Snowflake with Visa Sponsorship
AI Engineer jobs at Snowflake involve building and scaling the data infrastructure that powers enterprise machine learning. The company has a consistent track record of sponsoring work visas across engineering functions, making it a realistic target if you're on F-1 OPT, H-1B visa, or another employer-sponsored pathway.
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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.
We are seeking experienced professionals with a strong background in Artificial Intelligence, Machine Learning, and Cloud Architecture to join our Services Delivery team to help create exciting new offerings and capabilities for our customers!
In this strategic role, you will help customers expand their use of the Snowflake Data Cloud to bring AI/ML pipelines from ideation to full production. Leveraging Snowflake’s native features and extensive partner ecosystem, you will advise clients on best practices for scaling production-ready workloads. You will design tailored AI/ML solutions, coordinate closely with customer teams and Systems Integrators, and provide the technical leadership and oversight needed to ensure successful outcomes.
AS A PRINCIPAL SOLUTIONS ARCHITECT AT SNOWFLAKE, YOU WILL:
- Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload and provide customers with best practices given Snowflake's technology stack.
- Work with customers to understand their AI/ML use case, discover key requirements, and architect a Snowflake-centric solution to be delivered by Services Delivery.
- Understand how to build, deploy and AI and ML pipelines using Snowflake features and/or Snowflake ecosystem based on customer requirements.
- Work hands-on where needed using SQL, Python, and Cortex AI features to build POCs that demonstrate implementation techniques and best practices on Snowflake technology within the AI/ML workload.
- Follow best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own.
- Maintain deep understanding of competitive and complementary technologies and vendors within the AI/ML space, and how to position Snowflake in relation to them.
- Provide guidance on how to resolve customer-specific technical challenges.
- Support other members of the Services Delivery team develop their expertise.
- Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing.
OUR IDEAL SOLUTION ARCHITECT - AI/ML WILL HAVE:
- Minimum 5 years experience working with customers in a pre-sales or post-sales technical role.
- Outstanding skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
- Thorough understanding of the common generative AI and agent lifecycles including document ingestion, vector embedding selection, llm selection and optimization, genAI monitoring and evaluation techniques.
- Thorough understanding of the complete ML life-cycle including feature engineering, model development, model deployment and model management.
- Strong understanding of AI/MLOps, coupled with technologies and methodologies for deploying and monitoring models and agents.
- Experience and understanding of at least one public cloud platform (AWS, Azure or GCP).
- Experience with at least one AI/ML platform such as AWS Sagemaker, Databricks, GCP and Vertex AI, AzureML, Dataiku, Datarobot, etc.
- Hands-on scripting experience with SQL and at least one of the following; Python, Java or Scala.
- Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn, LangChain/LangGraph, LlamaIndex or similar.
- University degree in data science, computer science, engineering, mathematics or related fields, or equivalent experience.
BONUS POINTS FOR HAVING:
- Experience with Databricks/Apache Spark.
- Experience implementing data pipelines using ETL tools.
- Proven success at enterprise software.
- Vertical expertise in a core vertical such as FSI, Retail, Manufacturing etc.
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
The following represents the expected range of compensation for this role:
- The estimated base salary range for this role is $196,000 - $257,200.
- Additionally, this role is eligible to participate in Snowflake’s bonus and equity plan.
The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.
To comply with pay transparency requirements and other statutes, you can notify us if you believe that a job posting is not compliant by completing this form.
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Get Access To All JobsTips for Finding AI Engineer Jobs at Snowflake
Frame your ML experience around data pipelines
Snowflake's AI Engineering roles center on large-scale data processing, not just model development. Highlight experience with distributed systems, feature stores, or LLM inference pipelines to match the technical profile their hiring managers screen for.
Target teams building Cortex and Snowpark
Snowflake's AI product surface is concentrated in Cortex AI and Snowpark for Python. Applying to roles tied to these products signals genuine platform knowledge and puts you in front of teams that have actively grown their engineering headcount.
Start OPT applications before your graduation date
USCIS recommends filing OPT applications up to 90 days before your program end date. If you're targeting a Snowflake new-grad cohort, late filing shrinks your authorized work window and can complicate your start date alignment with their onboarding cycles.
Clarify H-1B cap timing during offer negotiations
H-1B cap-subject petitions can only be filed for an October 1 start. If Snowflake extends an offer outside the lottery window, confirm whether they'll bridge you on OPT STEM extension or use cap-exempt status to avoid a gap in authorization.
Use Migrate Mate to filter verified AI Engineer openings
Snowflake posts AI Engineer roles across multiple teams at different seniority levels. Use Migrate Mate to filter active openings by visa type so you're applying to positions that match your current immigration status and sponsorship needs.
Prepare your credentials before the PERM labor certification stage
If Snowflake pursues an EB-2 or EB-3 Green Card for you, DOL's PERM process requires documented proof of your qualifications. Gather official transcripts, employment records, and any credentials evaluations early so the filing isn't delayed by missing paperwork.
Frequently Asked Questions
Does Snowflake sponsor H-1B visas for AI Engineers?
Yes, Snowflake sponsors H-1B visas for AI Engineers. The company participates in the annual H-1B cap lottery and supports both initial petitions and transfers for engineers already in H-1B status. If you're cap-subject, your employment start date will align with the October 1 fiscal year start, so factor that into your offer timeline.
How do I apply for AI Engineer jobs at Snowflake?
Applications go through Snowflake's careers portal, where AI Engineer roles are listed by team and seniority level. Migrate Mate aggregates these openings and lets you filter by visa sponsorship type, which saves time if you need to confirm a role supports your specific status before applying. Tailor your resume to the specific product area the role supports.
Which visa types does Snowflake commonly use for AI Engineers?
Snowflake sponsors H-1B, F-1 OPT, F-1 CPT, TN visa, J-1 visa, and employment-based Green Cards including EB-2 and EB-3 for AI Engineers. F-1 candidates on STEM OPT get a 24-month extension beyond the standard 12 months, which gives Snowflake and the employee more runway before an H-1B lottery cycle is needed.
What qualifications does Snowflake expect for AI Engineer roles?
Snowflake's AI Engineer positions typically require a bachelor's or master's degree in computer science, machine learning, or a related engineering field. Beyond credentials, the teams prioritize hands-on experience with large-scale data systems, Python-based ML frameworks, and cloud infrastructure. Roles tied to Cortex AI or Snowpark often expect familiarity with LLM tooling and vector search.
How do I understand the H-1B petition timeline for a Snowflake offer?
USCIS opens H-1B cap registration in March each year, with lottery selection announced shortly after. If selected, Snowflake files your full petition between April and June for an October 1 start. If you're currently on OPT or STEM OPT, confirm with your Snowflake recruiter that your work authorization covers the gap between your start date and October 1.