Applied AI Engineer

Requirements

• 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

Nice to Haves

• 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

What You'll Be Doing at Snowflake

• 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

Perks and Benefits

• Join us in shaping the future of AI and data cloud technology
• Work with cutting-edge AI tools and technologies while solving complex challenges for enterprise customers
• Drive innovation at scale and work with leading organizations
• Access to Snowflake's advanced AI capabilities and infrastructure