Why This Job is Featured on The SaaS Jobs
Snowflake sits in the modern data-platform layer of SaaS, where product value is delivered through cloud-native capabilities rather than packaged software. Featuring a Senior AI/ML Architect within Applied Field Engineering highlights how AI adoption in SaaS is increasingly shaped at the intersection of product capabilities, customer data realities, and real-world implementation constraints—especially when the “platform” is the product.
From a SaaS career perspective, this kind of role builds durable platform fluency: translating AI/ML concepts into deployable architectures, running proof-of-concept work that proves adoption paths, and feeding customer learnings back into roadmap influence. The mix of solution design, technical storytelling, and reusable collateral creation mirrors how leading SaaS companies scale expertise across regions and segments, not just across individual accounts.
This position tends to suit professionals who enjoy being the technical authority in customer-facing settings while staying close to product and engineering. It aligns well with architects or senior practitioners who want to operate across multiple industries and use cases, and who are motivated by shaping how AI features are understood, evaluated, and operationalized in enterprise SaaS environments.
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
Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level.
Our Solution Engineering organization is seeking an AI Specialist who can provide hands-on expertise and support while working with technical decision makers and data scientists to design and architect AI solutions built on the Snowflake AI Data Cloud.
This is a strategic role that works closely with cross-functional teams, including product, engineering, and the broader field organization to ensure successful execution and customer adoption of Snowflake’s AI & ML solutions.
IN THIS ROLE YOU WILL GET TO:
Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the APJ region.
Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases.
Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback.
Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos.
Influence, tailor and maintain Solution Engineering AI and ML selling assets, including customer presentations, demonstrations, and customer stories.
Work with account teams across APJ region to help customers adopt AI/ML use cases on Snowflake
ON DAY ONE, WE WILL EXPECT YOU TO HAVE:
5+ years of experience building and deploying machine learning and generative AI solutions in the cloud.
Familiarity and associated knowledge of generative AI techniques like RAG, few shot learning, prompt engineering, or fine-tuning that are used to operationalize enterprise AI use cases like interactive chat applications or text processing.
Deep knowledge of Python and common ML packages (such as LangChain, pandas, sklearn, and PyTorch) as well as data engineering tools and technologies like dbt, Airflow, and Spark.
Strong presentation skills to both technical and executive audiences, whether whiteboarding sessions or formal readouts and demos.
Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent experience preferred.
BONUS POINTS FOR EXPERIENCE WITH THE FOLLOWING:
Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
Experience and understanding of large-scale infrastructure-as-a-service platforms (e.g. AWS, Microsoft Azure, GCP, etc.)
1+ years of practical Snowflake experience.
Knowledge of and experience with large-scale database technology (e.g. Snowflake, Netezza, Exadata, Teradata, Greenplum, etc.)
Working experience with quota carrying roles in the past.
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
