Principal Solutions Architect - AI/ML - Services Delivery
Primary stack
Nice to have's
Job description
About the Position
Principal Solutions Architect - AI/ML - Services Delivery
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.
Responsibilities
- Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload and provide customers with best practices given Snowflakes 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.
Requirements
- 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.
Nice to Have
- 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.
We Offer
- Competitive salary range: $160K – $210K.
- Remote work options.
About the Company
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.
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.
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
© Snowflake. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.
Cloud Computing,Data Management,Artificial Intelligence
About the Company Snowflake is a cloud-native data platform launched in 2012 by a team of data experts who identified limitations in traditional databases. The company has a strong presence in Poland, with a technical hub in Warsaw. Snowflake offers an international work environment with opportunities for skill development and collaboration with industry experts. Products, Services & Tech Stack Core Solutions: Data processing and management platform. Technologies & Frameworks: Specific technologies and frameworks are not detailed in the provided text. Project Scope & Target Clients Client Base: Not specified. Engineering Scale: Not specified.
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