Snowflake

AI

AppliedAIEngineer

Warsaw, Poland FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Applied AI Engineer at Snowflake. Skills: Applied AI Engineering, Enterprise AI solutions, AI agents, LLMs, Python, SQL, ML pipelines, Productionizing AI at Scale, MLOps. 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.”

What You'll Achieve.

Drive Customer Impact; Deliver with Velocity; Productionize AI at Scale; Be a Strategic Technical Advisor; Ensure Operational Excellence; Collaborate to Innovate

Industry & Context.

AI
Problems you'll solve

A passion for tackling complex and ambiguous technical challenges; solving problems and accelerate your impact; solve real-world business problems at a massive scale; solving our customers' most complex business challenges; Translate ambiguous business objectives into robust, scalable, and performant solutions; Excellent problem-solving skills

What They're Looking For.

Must Have

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 Have

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)., understanding of data warehousing principles, architecture, and best practices., Experience in a customer-facing role (e. g. , solutions architect)., Startup experience

What You'll Do.

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.

and ship high-quality code and ML pipelines.

Translate ambiguous business objectives into robust

and performant solutions using Python and SQL.

Own the full lifecycle of AI solution implementation

from developing prototypes to deploying

and optimizing them in secure

large-scale production environments.

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.

Architect and implement rigorous data validation

maintain strict SLA observability

and manage complex system interdependencies to guarantee reliable AI performance.

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.

How You'll Work.

Team & Collaboration

Partner directly with customer data science and engineering teams, serving as a technical expert and trusted advisor.; 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.

Communication Scope

Excellent communication skills; ability to articulate complex technical concepts to diverse stakeholders

Process & Methodology

Own the end-to-end lifecycle from prototype to production, Own the full lifecycle of AI solution implementation

Full Job Description

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 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 optimi

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