Why This Job is Featured on The SaaS Jobs
This Solutions Architect (AI/ML) role sits at the intersection of cloud data platforms and applied machine learning—an area where many SaaS products are being differentiated today. Positioned within Professional Services, it reflects a common SaaS pattern: translating a platform’s capabilities into repeatable customer outcomes, especially as AI/ML workloads move from experimentation into production-grade deployments.
For a SaaS career, the work builds durable platform expertise that travels across modern data stacks: designing reference architectures, integrating partner tools, and operationalising MLOps practices inside customer environments. The emphasis on proof-of-concepts, best practices, and knowledge transfer signals exposure to the full adoption lifecycle—how technical decisions affect time-to-value, governance, and long-term product usage. Collaboration with Product Management and Engineering also provides a line of sight into how field learnings shape roadmap and enablement.
This position suits professionals who prefer hands-on technical delivery combined with stakeholder communication, and who enjoy working across SQL/Python, APIs, and cloud services rather than staying in a single codebase. It aligns well with architects or senior practitioners who want customer-facing breadth in AI/ML implementations while staying anchored in a core SaaS platform ecosystem.
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.
We are looking for people who have a strong background in data science and cloud architecture to join our AI/ML Workload Services team to create exciting new offerings and capabilities for our customers! This team within the Professional Services group will be working with customers using Snowflake to expand their use of the Data Cloud to bring data science pipelines from ideation to deployment, and beyond using Snowflake's features and its extensive partner ecosystem. The role will be highly technical and hands-on, where you will be designing solutions based on requirements and coordinating with customer teams, and where needed Systems Integrators.
AS A SOLUTIONS ARCHITECT - AI/ML AT SNOWFLAKE, YOU WILL:
Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload
Build, deploy and ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements
Work hands-on where needed using SQL, Python, and APIs to build POCs that demonstrate implementation techniques and best practices on Snowflake technology for GenAI and ML workloads
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
Work with System Integrator consultants at a deep technical level to successfully position and deploy Snowflake in customer environments
Provide guidance on how to resolve customer-specific technical challenges
Support other members of the Professional Services team develop their expertise
Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing
Ability and flexibility to travel to work with customers on-site 25% of the time
OUR IDEAL SOLUTION ARCHITECT - AI/ML WILL HAVE:
Minimum 10 years experience working with customers in a pre-sales or post-sales technical role
Skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos
Thorough understanding of the complete Data Science life-cycle including feature engineering, model development, model deployment and model management.
Strong understanding of MLOps, coupled with technologies and methodologies for deploying and monitoring models
Experience and understanding of at least one public cloud platform (AWS, Azure or GCP)
Experience with at least one Data Science tool such as Sagemaker, AzureML, Vertex, Dataiku, DataRobot, H2O, and Jupyter Notebooks
Experience with Large Language Models, Retrieval and Agentic frameworks
Hands-on scripting experience with SQL and at least one of the following; Python, R, Java or Scala.
Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn or similar
University degree in computer science, engineering, mathematics or related fields, or equivalent experience
BONUS POINTS FOR HAVING:
Experience with Generative AI, LLMs and Vector Databases.
Experience with Databricks/Apache Spark, including PySpark
Experience implementing data pipelines using ETL tools
Experience working in a Data Science role
Proven success at enterprise software
Vertical expertise in a core vertical such as FSI, Retail, Manufacturing etc.
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
