Staff/Principal AI Software Engineer - Snowflake CoWork
Staff/Principal AI Software Engineer · Principal · Full Time
Opens Snowflake's application page
Role
What you'll do.
Join Snowflake's Cortex CoWork team as a Principal AI Engineer to define the technical vision for enterprise AI products like Snowflake Intelligence. This role combines hands-on expertise in LLM orchestration, agentic reasoning, and NL-to-SQL systems with strategic leadership responsibilities, requiring 10+ years of software engineering experience with 3+ years leading large-scale LLM application deployments.
Responsibilities
- Technical Strategy and Architecture Leadership: Define the long-term technical vision for Snowflake Intelligence and lead architectural design of multi-agent systems, complex tool-use frameworks, and self-correcting natural language-to-SQL engines that power Fortune 500 enterprises.
- Drive Enterprise-Scale Reliability: Establish and implement world-class automated evaluation infrastructure and hill-climbing methodologies for measuring and guaranteeing large language model performance across diverse customer schemas at massive production scale.
- Cross-Functional Technical Influence: Partner with Product and Engineering leadership to align advanced AI capabilities with business objectives, bridging the gap between research-driven LLM modeling and production infrastructure to ensure breakthrough capabilities are viable at Snowflake's scale.
- Ecosystem Architecture and Extensibility: Design scalable context engineering patterns, advanced function calling frameworks, and semantic layer integrations that enable other Snowflake teams and external developers to build innovative AI-driven solutions.
- Technical Leadership and Mentorship: Act as a force multiplier by mentoring Staff and Senior engineers, leading high-stakes cross-functional strike teams on complex AI initiatives, and fostering a culture of technical excellence, rapid experimentation, and innovation.
- LLM Orchestration and Optimization: Apply deep expertise in LLM orchestration, prompt optimization, semantic modeling, and robust guardrail design for non-deterministic systems to ensure reliable AI product delivery.
Qualifications
What we look for.
Technical
LLM Orchestration Expertise
Deep, production-level understanding of large language model orchestration patterns, including multi-agent architectures, tool-use frameworks, and reasoning systems.
Natural Language-to-SQL Specialization
Expert-level knowledge of NL-to-SQL systems, including query generation, semantic understanding, schema mapping, and performance optimization for enterprise data warehouses.
Prompt Engineering and Optimization
Advanced expertise in prompt design, optimization techniques, few-shot learning, chain-of-thought patterns, and other sophisticated prompt engineering methodologies.
Retrieval-Augmented Generation (RAG)
Comprehensive understanding of enterprise-scale RAG systems, including semantic search, context retrieval, knowledge base design, and integration with large language models.
AI System Reliability and Evaluation
Proficiency in designing evaluation frameworks, building automated testing infrastructure, implementing guardrails for non-deterministic systems, and measuring LLM performance metrics.
Data Stack Integration
Deep expertise integrating AI systems with modern data platforms, including data warehouses, semantic layers, SQL engines, and analytics infrastructure.
Education
Advanced Degree in Computer Science or AI
Bachelor's, Master's, or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field from an accredited institution.
Experience
Senior Software Engineering Background
10+ years of progressive software engineering experience with demonstrated expertise in designing, building, and shipping large-scale systems.
LLM-Based Application Leadership
3+ years of hands-on experience leading the deployment and optimization of large language model-based applications at enterprise scale, managing production systems serving millions of users.
Principal-Level Technical Leadership
Proven track record of holding a Principal, Staff, or equivalent high-level individual contributor role, or leading the technical launch of a major AI product adopted at enterprise scale.
Complex Systems Integration
Demonstrated success designing and implementing complex systems that integrate AI with traditional data stacks including SQL engines, retrieval systems, and semantic layers.
Skills
Required
LLM Architecture and Orchestration
Expert-level design and implementation of large language model systems including multi-agent frameworks, function calling, and reasoning chains in production environments.
AI Systems Reliability Engineering
Designing evaluation methodologies, automated testing infrastructure, performance monitoring, and guardrails for enterprise AI systems.
Complex Systems Design
Architecting scalable, reliable systems that integrate machine learning with traditional software engineering practices and data infrastructure.
Strategic Technical Communication
Exceptional ability to articulate complex technical trade-offs, system architecture decisions, and AI capabilities to both executive stakeholders and technical individual contributors.
Cross-Functional Leadership
Leading and influencing across product, engineering, and research teams while maintaining technical credibility and driving consensus on technical direction.
Python Programming
Advanced Python development for building AI systems, orchestration logic, evaluation frameworks, and integration with machine learning libraries.
SQL and Data Querying
Deep expertise in SQL, query optimization, schema design, and understanding enterprise data modeling for semantic layer integration.
Preferred
Vector Database Experience
Nice to haveHands-on experience with vector databases and semantic search technologies for implementing enterprise-scale RAG systems.
Applied ML and Model Fine-tuning
Nice to haveExperience with prompt optimization, model fine-tuning, retrieval optimization, and other techniques for improving LLM performance on specific domains.
Cloud Data Warehouse Expertise
Nice to haveDeep familiarity with Snowflake, BigQuery, or similar cloud data warehouses and their integration with AI/ML workloads.
Open Source AI Frameworks
Nice to haveContribution to or deep familiarity with LangChain, LlamaIndex, or similar orchestration frameworks for building production AI applications.
Distributed Systems Knowledge
Nice to haveExperience designing highly available, fault-tolerant systems that operate at scale and manage complex distributed state.
Research Publication or Patent Portfolio
Nice to havePublished research papers or patents in machine learning, natural language processing, or related AI domains demonstrating thought leadership.
Startup or Fast-Growth Company Experience
Nice to haveExperience in high-velocity environments where you've helped define technical direction and scaled engineering teams rapidly.
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 264,000 – 379,500
Equity·Stock options
Benefits
Competitive Equity Compensation
Substantial stock options aligned with company growth, reflecting the significant value creation opportunity at Snowflake's scale and market position.
Comprehensive Health and Wellness
Full medical, dental, and vision coverage with industry-leading plans, plus wellness programs, mental health support, and fitness benefits.
Retirement Planning
401(k) plan with company match and financial planning resources to support long-term wealth building.
Unlimited Paid Time Off
Flexible vacation policy with the ability to take time off as needed, supporting work-life balance and personal wellbeing.
Professional Development
Learning budgets, conference attendance, advanced training programs, and mentorship opportunities to accelerate your technical growth and career advancement.
Parental Leave
Generous parental leave benefits supporting both birth and adoptive parents with job-protected time off.
Remote Work Flexibility
Hybrid or fully remote work arrangements with access to collaborative office spaces in major tech hubs and company campuses.
Employee Stock Purchase Plan
Opportunity to purchase company stock at a discount, further aligning employee interests with company success.
Process
Interview steps.
- 01
Initial Screening with Recruiter
30-minute call with Snowflake recruiter to discuss background, career trajectory, interest in the Cortex CoWork team, and alignment with the Principal-level AI engineering role.
- 02
Technical Deep Dive - LLM Architecture
60-90 minute session with one or two Principal/Staff engineers focusing on your experience designing LLM-based systems, architectural decisions, trade-offs between different orchestration approaches, and lessons learned from production deployments.
- 03
System Design and Evaluation Frameworks
60-minute technical interview discussing how you would design evaluation infrastructure for LLM systems, implement reliability guarantees, and build hill-climbing mechanisms for improving model performance at scale.
- 04
Product and Business Acumen
45-60 minute session with Product Manager and/or Snowflake business leader exploring your understanding of enterprise AI challenges, market dynamics, and how you would prioritize technical investments to drive customer value.
- 05
Leadership and Cross-Functional Collaboration
45-minute conversation with VP or Director-level engineering leader assessing your experience mentoring engineers, influencing across teams, and establishing technical vision in organizations.
- 06
Founder/Executive Leadership Conversation
30-45 minute final conversation with Snowflake executive leadership to discuss long-term vision, cultural fit, and strategic perspectives on the future of AI in enterprise data.
Full posting
Original listing.
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.
The Cortex CoWork team is defining the future of AI for enterprise data. Our mission is to transform how the world’s largest enterprises interact with their data through flagship products like Snowflake (CoWork) Intelligence.
As a Principal AI Engineer, you will be a technical North Star for our AI initiatives. You won't just execute on a roadmap; you will help define it. You will tackle the most complex, "frontier" problems in agentic reasoning, NL-to-SQL, and enterprise-scale RAG, ensuring our AI products are not only innovative but fundamentally reliable and scalable for the Fortune 500.
What you will do in this role:
Technical Strategy & Architecture: Define the long-term technical vision for Snowflake Intelligence. Lead the architectural design of multi-agent systems, complex tool-use frameworks, and self-correcting NL-to-SQL engines.
Drive Industry-Leading Reliability: Move beyond simple evals to build world-class, automated "hill-climbing" infrastructure. You will establish the methodology for how Snowflake measures and guarantees LLM performance across diverse customer schemas.
Cross-Functional Influence: Partner with Product and Engineering leadership to align AI capabilities with business goals. You will bridge the gap between Research (modeling) and Production (infra), ensuring the latest LLM breakthroughs are viable at Snowflake scale.
Ecosystem Thinking: Design extensible "context engineering" patterns—including advanced function calling and semantic layer integration—that can be leveraged by other Snowflake teams and external developers.
Technical Leadership & Mentorship: Act as a force multiplier. You will mentor Staff and Senior engineers, lead cross-functional "strike teams" on high-stakes projects, and foster a culture of technical excellence and rapid experimentation.
Requirements:
Experience: 10+ years of software engineering experience, with 3+ years specifically leading the deployment of LLM-based applications at massive scale.
Education: Bachelor’s, Master’s, or PhD in Computer Science, AI, or a related field.
Expertise: Deep, "under-the-hood" understanding of LLM orchestration. You should be an expert in prompt optimization, semantic modeling, and building robust guardrails for non-deterministic systems.
Systems Thinking: Proven track record of designing complex systems that integrate AI with traditional data stacks (SQL, Retrieval Systems, Semantic Layers).
Communication: Exceptional ability to communicate complex technical trade-offs to both executive leadership and ICs. You are as comfortable in a design doc as you are in a boardroom.
Proven Impact: You have previously held a "Principal" or equivalent high-level IC role, or have led the technical launch of a major AI product used by millions.Staff/Principal AI Software Engineer - Snowflake CoWork
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.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
Redirects to Snowflake's application page.
Other roles
More at Snowflake.
Software Engineer AI Team
Mid
Sr Manager, Applied Field Engineering - AI/ML
Manager
Principal Data Platform Architect
Principal
Senior Software Engineer - NatSec
Senior
Senior Engineering Manager - OLTP
Senior