> Markdown version of [/jobs/ext/1742180-senior-ai-engineer](https://www.wearedevelopers.com/jobs/ext/1742180-senior-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Snowflake Inc. - **Location:** Menlo Park, CA, United States - **Experience:** Expert - **Salary:** $156,000.0 - $224,200.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Business Logic, Software Applications, ARM Architecture, Automated Storage and Retrieval Systems, Big Data, Data Infrastructure, Software Debugging, Python (Programming Language), Machine Learning, Recommender Systems, Standard Sql, Software Deployment, Enterprise Data Management, Large Language Models, Snowflake, Prompt Engineering, Data Layers, Automation Anywhere - **Published:** July 3, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17476190?backUrl=%2Fcareer%2F17476190%2FSenior-Ai-Engineer-California-Menlo-Park ## About the Role * Hands-on experience building and shipping applied AI or LLM-based systems for real user workflows * Demonstrated ability to independently own and deliver production-grade AI applications or workflow automation solutions for a business function or product area * 5+ years of experience in applied AI, machine learning engineering, data applications, or related technical roles * Strong Python and SQL skills, plus comfort working with data-intensive applications and modern data platforms * Experience with prompt design, evaluation, observability, orchestration, and production hardening for AI systems * Experience building systems that combine AI capabilities with semantic layers, retrieval systems, or other knowledge-rich workflows * Good judgment in turning ambiguous business problems into scoped, iterative deliverables * Experience collaborating directly with business stakeholders and translating workflow pain points into product solutions * Strong communication skills and a bias toward shipping, learning, and iterating * A quality mindset around testing, measurement, reliability, maintainability, and responsible use of enterprise data * Experience operating effectively in fast-moving, ambiguous environments with changing priorities Nice to Have * Experience with Snowflake platform capabilities, including Cortex and related AI workflows * Experience building internal AI assistants, recommendation features, workflow automation, or decision-support applications * Familiarity with GTM, sales productivity, marketing operations, customer support, or business process automation domains * Experience working with trusted semantic layers, retrieval systems, and AI systems grounded in enterprise data * Familiarity with analytics engineering, data modeling, or governed enterprise data architectures * Experience translating internal implementation learnings into repeatable patterns, platform requirements, or product feedback Snowflake is growing fast, and we're scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. ## Description We are seeking a Senior AI Engineer to build AI-powered applications and workflows that accelerate Snowflake's go-to-market teams. This role sits within Data, Analytics & AI and focuses on turning ambiguous business problems into production-ready AI applications that improve how Snowflake teams work every day. The right candidate combines strong applied AI instincts with practical software, data, and product judgment, and is excited to partner closely with business stakeholders to ship systems that are useful, reliable, and measurable. Within DAA, this role helps advance Snowflake's internal AI transformation by building high-impact GTM applications and workflows, improving how teams use data and AI in practice, and helping shape scalable patterns for future solutions. This role will help Snowflake act as Customer Zero for AI-powered GTM workflows by applying modern LLM capabilities and Snowflake AI products to real internal use cases, learning from adoption in production, and translating those learnings into scalable patterns and actionable product feedback. What You'll Do * Design, build, and maintain AI applications, and workflow automation tools for GTM use cases across the full product lifecycle, from problem definition and prototyping through production deployment, iteration, and ongoing support * Independently scope and deliver medium-sized projects, and contribute meaningfully to larger cross-functional initiatives * Translate ambiguous business needs into practical technical plans, balancing speed, maintainability, quality, and long-term architecture * Partner closely with teams such as Sales, Marketing, Customer Support, Product, and Engineering to understand workflow pain points and deliver solutions that improve productivity, decision-making, and execution * Apply modern LLM capabilities and Snowflake AI products in production-oriented ways to solve real business problems, including knowledge-rich workflows, internal copilots, recommendation systems, and decision-support applications * Work across the data, application, and AI stack, including semantic layers, retrieval systems, orchestration patterns, evaluation, and application logic * Build AI systems grounded in trusted enterprise data and strong engineering practices, with attention to reliability, observability, testing, measurement, and maintainability * Own production quality for delivered solutions, including debugging, monitoring, issue triage, and continuous improvement based on user feedback and operational signals * Help Snowflake act as Customer Zero by turning internal usage insights, workflow learnings, and implementation challenges into actionable feedback for product and platform teams * Contribute to team quality through strong documentation, reusable patterns, automation, and thoughtful engineering standards * Act as a go-to engineer in at least one area, help diagnose issues beyond your immediate domain, and mentor more junior teammates * Communicate clearly with stakeholders on scope, tradeoffs, timelines, risks, and outcomes ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) - [How to govern Vibe Coding for the Enterprise](https://www.wearedevelopers.com/videos/100290-how-to-govern-vibe-coding-for-the-enterprise) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? 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