Staff Applied AI Engineer

Snowflake is a company focused on empowering enterprises to achieve their full potential by building impactful AI solutions. The role is part of the Cortex AI team, working with the world's most innovative companies to unlock the power of AI.

Minimum Qualifications:

• Demonstrated experience leading technical projects or teams, including setting technical direction, reviewing work, and driving delivery to completion.
• Excellent problem-solving and communication skills, able to articulate complex technical concepts to technical and executive stakeholders.
• Comfort with ambiguity and ability to independently structure and execute on complex, open-ended problems.
• Proven experience building and productionizing applications using LLMs, especially with technologies like RAG and agentic workflows.
• 8+ years of professional software engineering experience.

Preferred Qualifications:

• Hands-on experience with the MLOps lifecycle, including model deployment, monitoring, and evaluation in cloud environments (AWS, Azure, or GCP).
• Familiarity with core data science libraries and tools such as pandas, numpy, and Snowpark.
• Experience in a customer-facing technical role.
• Experience defining and executing AI project roadmaps across multiple concurrent engagements or customers.
• Startup experience or experience in a high-growth, fast-paced environment.

Lead Customer Programs:

• Own the full lifecycle of complex, multi-engineer AI engagements from scoping and architecture through deployment, monitoring, and handoff.
• Be accountable for delivery quality and customer outcomes across a portfolio of strategic accounts.

Grow and Mentor Engineers:

• Provide day-to-day technical leadership and mentorship to a team of 2–4 Applied AI Engineers.
• Review designs and code, unblock teammates, and actively develop their skills and careers.

Deliver with Velocity:

• Remain a hands-on contributor designing, iterating, and shipping high-quality ML pipelines and agentic AI solutions.
• Translate ambiguous business objectives into robust, scalable, and performant solutions.

Productionize AI at Scale:

• Own the full implementation lifecycle for AI solutions, from prototypes to deployment, monitoring, and optimization in secure, large-scale production environments.
• Define evaluation frameworks, safety guardrails, observability, and human-review workflows to keep AI applications reliable and trustworthy.

Be a Strategic Technical Advisor:

• Serve as a senior technical advisor to customer data science and engineering leadership.
• Set standards for Snowflake AI deployment and articulate complex technical concepts to technical and executive stakeholders.

Collaborate to Innovate:

• Work cross-functionally with Product and Engineering teams to bring real-world patterns and feedback to shape Snowflake's AI platform.

Drive Compounding Outcomes:

• Identify and champion improvements to team practices.
• Turn recurring deployment patterns into reusable assets, reference architectures, evaluation harnesses, and product feedback.

Have the opportunity to travel:

• Spend time onsite working closely with Snowflake’s most strategic customers.