Why This Job is Featured on The SaaS Jobs
This Senior AI/ML Architect role sits at the intersection of modern data platforms and the current wave of applied generative AI in SaaS. Snowflake’s positioning as an AI Data Cloud provider makes the work inherently ecosystem-facing, where technical choices must map to real customer architectures, governance expectations, and production constraints across cloud environments. The remit also reflects a mature SaaS organization’s need to translate platform capabilities into repeatable, field-ready solutions.
For a SaaS career, the durable value here is learning how AI features become adoptable products in the wild. The role touches solution architecture, proof-of-concept design, and the feedback loop back into product and engineering, which is a common pattern in scaled SaaS companies that sell to technical buyers. Experience packaging technical insight into collateral, demos, and narratives is also transferable across platform, developer tools, and data infrastructure categories.
This position tends to suit practitioners who enjoy being the technical authority in customer-facing settings while staying hands-on with ML and GenAI implementation details. It aligns with senior profiles that prefer cross-functional influence over narrow ownership, and with architects comfortable moving between executive communication, engineering depth, and iterative experimentation.
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.
Our Sales 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 Sales 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:
10+ years of experience building and deploying machine learning and 3+ years of building and deploying Generative AI solutions in the cloud.
Practitioner level hands-on experience on Machine Learning workload including MLOps, Feature Store, Model Deployment, Model Explainability and Observability
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
