Snowflake
AI
AppliedAIEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Applied AI Engineer at Snowflake. Skills: AI, LLM, Python, SQL. Architect AI solutions. Build AI solutions”
What You'll Achieve.
Deliver results; Achieve full potential; Build production-grade AI systems; Solve real-world business problems at scale; Raise the bar on accuracy, faithfulness, and safety; Continuously raise the bar on accuracy; Continuously raise the bar on faithfulness; Continuously raise the bar on safety; Compound quality over time; Drive down errors
Industry & Context.
Solve problems; Accelerate impact; Excellent problem-solving skills; Translate ambiguous customer goals into measurable quality metrics; Translate ambiguous business objectives into robust, scalable, and performant solutions; Failure-mode analysis on agent or RAG systems
Willingness to travel, Spend at least 25% of your time onsite, Follow company’s confidentiality and security standards, Abide by company’s data security plan, Keep customer information secure and confidential
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, Willingness to travel, Proven experience building applications using LLMs, Hands-on experience defining quality metrics and running evaluations for LLM or agent systems, Excellent problem-solving and communication skills, Comfort with ambiguity, Desire to thrive in a fast-paced, ever-changing Generative AI environment
Nice to Have
Experience building eval sets from production traces and synthetic data, Running structured experimentation (A tests, ablations, offline evals) to compare prompts, models, or agent architectures, Familiarity with eval and observability tooling (e. g. , Braintrust, LangSmith, Arize, Weave, Promptfoo), Experience building custom eval harnesses, Experience with failure-mode analysis on agent or RAG systems, Hands-on experience with the MLOps lifecycle, Model deployment, monitoring, and evaluation in a cloud environment (AWS, Azure, or GCP), Familiarity with core data science libraries and tools (e. g. , pandas, numpy, Snowpark), Experience in a customer-facing technical role (e. g. , solutions architect, sales engineer, or professional services), Startup experience
What You'll Do.
Architect AI solutions
Build sophisticated AI agents
Own end-to-end lifecycle
Prototype to production
Solve customer challenges
Define system quality
Translate goals to metrics
Run systematic eval loops
Hill-climb on agent quality
Raise bar on accuracy
Raise bar on faithfulness
Treat measurement as first-class
Iterate and ship code
Translate objectives to solutions
Build robust solutions
Build scalable solutions
Build performant solutions
Own implementation lifecycle
Prototype through deployment
Build safety guardrails
Build human-review workflows
Keep AI applications reliable
Keep AI applications trustworthy
Close loop from production traces
Close loop from user feedback
Compound quality over time
Partner with customer teams
Leverage AI for business
Collaborate to innovate
Share real-world feedback
Influence AI platform future
Work closely with customers
How You'll Work.
Team & Collaboration
Partner directly with customer data science and engineering teams; Collaborate cross-functionally with Snowflake's Product and Engineering teams; Share real-world feedback from the field to directly influence the future of Snowflake's AI platform; Work closely with Snowflake's most strategic customers
Communication Scope
Ability to articulate complex technical concepts to diverse stakeholders
Process & Methodology
Own the end-to-end lifecycle of your workstreams – from prototype to production
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. Snowflake is about empowering enterprises to achieve their full potential – and people too. With a culture that's all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology – and careers – to the next level. Where Data Does More. Join the Snowflake team. 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 on our Cortex AI team, you will be a hands-on builder and a key technical partner to our most strategic customers, placing you at the forefront of the enterprise AI revolution. You won't just work with cutting-edge technology – you'll deploy it to solve real-world business problems at scale, building production-grade AI systems using Snowpark, Cortex, and our native LLM capabilities. IN THIS ROLE AT SNOWFLAKE, YOU WILL: Build Customer Solutions: Architect, build, and deploy enterprise-grade AI solutions, including sophisticated AI agents. Own the end-to-end lifecycle of your workstreams – from prototype to production – directly solving customers' most complex business challenges. Own the Quality of What You Ship: Define what "good" means for the systems you build. Translate ambiguous customer goals into measurab
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