Software Engineer, Applied AI

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.

At Snowflake, we are building a high-impact team to help the world’s most innovative companies unlock the power of AI. As a Forward Deployed Engineer, Applied AI 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. Build and iterate on AI pipelines and agents within a team-led engagement from prototype to production, contribute to evaluation frameworks and observability infrastructure 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.

- Have a real opportunity for growth: Junior/Mid Engineers focus on building. As you demonstrate engineering judgment, communication, and cross-team impact, you take on progressively larger ownership: first a component, then a workstream, then a customer engagement. Senior Engineer promotion requires running a scoped customer working session independently and owning a workstream end-to-end - observable, coachable milestones, not a vague seniority bar.

WE'RE LOOKING FOR CANDIDATES WHO HAVE:

Minimum Qualifications:

- 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.

- Hands-on experience building and shipping LLM-based or ML applications.

- Proven hands-on experience with data modeling, ETL/ELT development, and performance tuning.

- Advanced proficiency in Python, Java, C++ or other programming languages 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.

Preferred Qualifications:

- Proven experience building and production 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

WHY JOIN OUR TEAM AT SNOWFLAKE?

Join us in shaping the future of AI and data cloud technology. You'll work with cutting-edge AI tools and technologies while solving complex challenges for enterprise customers. Our team offers the unique opportunity to drive innovation at scale, w