Rocket
Mini tools
Applied AI Engineer
Snowflake
On-site
Menlo Park, CA, United States
Full-time
$157,000 -
$230,000
About Snowflake
Snowflake is the Data Cloud company, empowering organizations of all sizes to mobilize their data with near-unlimited scale, performance, and security. By eliminating silos and enabling seamless collaboration, Snowflake helps businesses unlock the true value of their data for faster insights, smarter decisions, and greater innovation — all on a fully managed platform built for the cloud.
About the Role
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/ML 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 Snowpark, Cortex, and our native LLM capabilities.
Qualifications
Bachelor’s degree in Computer Science, Engineering, a related technical field, or equivalent practical experience.
3+ years of professional software engineering experience, with a strong command of Python.
A passion for tackling complex and ambiguous technical challenges, leveraging cutting-edge research and AI to deliver impactful solutions.
Experience building applications or pipelines that involve machine learning models or data-intensive systems.
Familiarity with core data science libraries and tools (e.g., pandas, numpy, Snowpark).
A desire to thrive in a fast-paced, dynamic environment and the ability to adapt quickly to the ever-changing world of Generative AI.
Preferred Qualifications:
Advanced degree (Master's or PhD) in a relevant field.
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).
Excellent problem-solving and communication skills, with an ability to articulate complex technical concepts to diverse stakeholders.
Experience in a customer-facing role (e.g., solutions architect, sales engineer, or professional services).
3+ years of professional software engineering experience, with a strong command of Python.
A passion for tackling complex and ambiguous technical challenges, leveraging cutting-edge research and AI to deliver impactful solutions.
Experience building applications or pipelines that involve machine learning models or data-intensive systems.
Familiarity with core data science libraries and tools (e.g., pandas, numpy, Snowpark).
A desire to thrive in a fast-paced, dynamic environment and the ability to adapt quickly to the ever-changing world of Generative AI.
Preferred Qualifications:
Advanced degree (Master's or PhD) in a relevant field.
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).
Excellent problem-solving and communication skills, with an ability to articulate complex technical concepts to diverse stakeholders.
Experience in a customer-facing role (e.g., solutions architect, sales engineer, or professional services).
Responsibilities
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.
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.
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.
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.
Benefits
This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.
