Applied AI Engineer
Indexed description
At Snowflake, we are building a high-impact team to help the world’s most innovative companies unlock the power of AI. As an Applied AI Engineer in our Cortex AI team, you will be a hands-on builder and a critical technical partner to our most strategic customers, placing you at the forefront of the enterprise AI revolution. You won't just be working with cutting-edge technology; you will be deploying it to solve real-world business problems at a massive scale. This role places you at the intersection of product, engineering, and customer success, building production-grade AI systems using Snowflake AI Platform, Cortex, and our native LLM capabilities.
IN THIS ROLE AT SNOWFLAKE, YOU WILL:
- Drive Customer Impact: Architect, build, and deploy enterprise-grade AI solutions, including sophisticated AI agents. Own the end-to-end lifecycle from prototype to production, directly solving our customers' most complex business challenges.
- Deliver with Velocity: Rapidly design, iterate, and ship high-quality code and ML pipelines. Translate ambiguous business objectives into robust, scalable, and performant solutions using Python and SQL.
- Productionize AI at Scale: Own the full lifecycle of AI solution implementation, from developing prototypes to deploying, monitoring, and optimizing them in secure, large-scale production environments.
- Be a Strategic Technical Advisor: Partner directly with customer data science and engineering teams, serving as a technical expert and trusted advisor on how to best leverage AI for their business challenges.
- Ensure Operational Excellence: Architect and implement rigorous data validation, maintain strict SLA observability, and manage complex system interdependencies to guarantee reliable AI performance.
- Collaborate to Innovate: Work cross-functionally with Snowflake’s Product and Engineering teams to share real-world feedback from the customers, directly influencing the future of Snowflake's AI platform.
- Bachelor’s degree in Computer Science, Engineering, a related technical field, or equivalent practical experience.
- 3+ years of professional software engineering experience,
- A passion for tackling complex and ambiguous technical challenges, leveraging cutting-edge research and AI to deliver impactful solutions.
- Experience building, evaluating and tuning applications and pipelines that involve machine learning models or data-intensive systems. Familiarity with core data science libraries and tools (e.g., pandas, numpy, Snowpark).
- Proven hands-on experience with data modeling, ETL/ELT development, and performance tuning.
- Advanced proficiency in Python, with experience scripting and automating data workflows.
- Excellent problem-solving and communication skills, with an ability to articulate complex technical concepts to diverse stakeholders.
- A desire to thrive in a fast-paced, dynamic environment and the ability to adapt quickly to the ever-changing world of Generative AI.
- Proven experience building and productionizing applications using LLMs, especially with technologies like RAG and agentic workflows.
- Hands-on experience with the MLOps lifecycle, including model deployment, monitoring, and evaluation in a cloud environment (AWS, Azure, or GCP).
- Strong understanding of data warehousing principles, architecture, and best practices.
- Experience in a customer-facing role (e.g., solutions architect).
- Startup experience
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
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