Director of Engineering, AI Functions
Snowflake4 days ago
Location
US-CA-Menlo Park
Type
Full Time
Salary
USD 304,000 – 437,000
Level
Director
Role
Director, Engineering
Posted
Jul 21, 2026
Full TimeDirector
The role
Summary
Director of Engineering, AI Functions at Snowflake is a hybrid director/principal engineer role leading the strategic vision and technical architecture for AI-powered SQL functions that democratize AI analytics. This position requires 10+ years of software engineering experience with 2+ years of engineering director/management experience, deep expertise in AI infrastructure, LLMs, and distributed systems, combined with proven ability to build and mentor high-performing technical teams at scale.
What you'll do
Architect and Own Technical Strategy: Create and own the architecture and design of the AI Functions product portfolio, influence the product roadmap, and identify new technical initiatives that push Snowflake's technology forward. This includes designing systems that seamlessly integrate advanced AI and LLM-powered functions into SQL, enabling customers to operationalize AI at scale within their existing workflows while handling the full AI lifecycle behind the scenes.
Set Strategic Vision and Drive Accountability: Establish the strategic vision for the engineering team, drive accountability for plans and deliverables, and ensure execution excellence. Set clear objectives aligned with Snowflake's mission to democratize AI by surfacing powerful AI functions directly in SQL for analyzing both structured and unstructured data with minimal configuration.
Solve Complex Business Problems at Scale: Apply strong software engineering and analytical problem-solving skills to address real business needs at scale. Lead the development of large-scale query processing and distributed systems capabilities that enable data analysts, engineers, and scientists to build AI-powered data transformation pipelines seamlessly within SQL workflows.
Drive Cross-Functional Product Initiatives: Lead engineering projects from ideation through full implementation in close partnership with product management, design, data science, and other cross-functional teams. Coordinate efforts to bring AI Functions to market while maintaining technical excellence and customer value delivery.
Foster Innovation Culture and Technical Excellence: Build and maintain a culture of creativity and innovation while ensuring sound, practical decision-making. Promote an experimental mindset across the team, encouraging rapid testing of emerging AI capabilities to discover simpler and more powerful ways to deliver results to customers.
Lead Organizational Development and Scaling: Direct organizational structure evolution to support growth and improve engineering efficiency. Design team structures that enable effective scaling as the AI Functions portfolio grows in scope and impact, ensuring the team remains agile and high-performing.
Build and Mentor Technical Leadership: Hire, develop, and mentor senior technical leaders and engineering managers. Create career growth opportunities for high-performing engineers, establish strong technical mentorship programs, and build a leadership pipeline that supports Snowflake's long-term growth and success.
Manage and Grow High-Impact Teams: Manage, grow, and mentor engineering teams that have significant impact on the overall Snowflake product success. Drive team performance, establish technical standards, and ensure alignment with company values around AI-native thinking, low-ego collaboration, and dynamic problem-solving.
What we look for
Technical
Distributed Systems ArchitectureExpert-level knowledge of distributed systems design patterns, consensus algorithms, scalability architectures, and fault tolerance mechanisms. Ability to architect systems that process petabyte-scale data across cloud infrastructure.
Large Language Model SystemsDeep technical understanding of LLM architecture, deployment strategies, optimization techniques, and integration patterns. Experience with prompt engineering, fine-tuning, retrieval-augmented generation (RAG), and production LLM serving infrastructure.
Query Processing and Database SystemsStrong expertise in query optimization, execution planning, SQL semantics, and database engine architecture. Understanding of columnar storage, query compilation, and performance optimization for analytical workloads at scale.
Cloud Data Platform ArchitectureExperience designing and building cloud-native data platforms that handle structured and unstructured data at scale. Familiarity with cloud data warehouse patterns, data lakes, and AI-ready data infrastructure.
AI/ML Systems IntegrationTechnical expertise in integrating machine learning and AI functions into core database or data platform systems. Experience with embedding AI capabilities into SQL or data manipulation languages for end-user accessibility.
Engineering Leadership and Organizational DesignProven expertise in engineering team leadership, organizational scaling, technical hiring, and mentorship. Ability to drive technical strategy, establish engineering culture, and make architectural decisions that shape product direction.
Education
Advanced Degree in Computer ScienceMaster's degree or Ph.D. in Computer Science, Computer Engineering, or related field required. This foundation provides deep understanding of algorithms, distributed systems, and computational theory essential for architecting large-scale AI infrastructure and query processing systems.
Experience
10+ Years Software Engineering ExperienceMinimum 10 years of professional software engineering experience with recent hands-on technical work. Must demonstrate deep expertise in designing and building scalable systems, with proven ability to architect solutions that handle massive data volumes and complex computational requirements.
2+ Years Engineering Director/Management ExperienceMinimum 2 years of experience as an Engineering Director or equivalent leadership role, including direct management of managers and multi-level teams. Must demonstrate ability to set technical vision, drive organizational alignment, and scale engineering organizations effectively.
Deep AI Infrastructure and LLM ExpertiseProven deep experience with AI infrastructure, machine learning systems, and Large Language Models. Should have hands-on experience building or leading teams that work with LLM deployment, optimization, and integration into production systems at enterprise scale.
Large-Scale Distributed Systems ExperienceStrong track record building large-scale query processing engines or distributed systems that handle massive data volumes. Experience with cloud data platforms, data warehousing, or similar systems architecture is highly valuable for this strategic role.
Technical Team Building and RecruitmentStrong demonstrated track record of recruiting, building, and growing high-performing technical teams. Must have successfully hired and developed senior engineers and technical leaders in competitive markets, with ability to build inclusive and innovative engineering cultures.
Skills
Required skills
Distributed Systems DesignExpert ability to architect and design large-scale distributed systems that scale to enterprise demands with reliability and performance requirements met across global deployments.
Large Language Model ExpertiseDeep technical knowledge of LLM capabilities, limitations, deployment patterns, and how to effectively integrate LLMs into production systems and data workflows.
Query Engine ArchitectureStrong expertise in building or leading development of query processing engines, including optimization, compilation, and execution planning for analytical workloads.
Engineering LeadershipDemonstrated ability to lead engineering teams, set technical vision, drive accountability for outcomes, and manage managers in multi-level organizational structures.
Strategic Technical VisionAbility to synthesize business requirements, market trends, and technical constraints to establish compelling technical direction and roadmap that aligns with company strategy.
Cross-Functional CollaborationExcellent communication and collaboration skills across product, data science, infrastructure, and global teams with ability to influence and align stakeholders on technical decisions.
Technical Recruitment and MentorshipProven ability to recruit top technical talent, build inclusive high-performing teams, and mentor senior engineers and technical leaders through coaching and career development.
Hands-On Software EngineeringAbility to remain technically current with hands-on contributions to architecture, design, and code review. Should actively engage in technical discussions and problem-solving despite management responsibilities.
Nice to have
Cloud Data Warehouse ExperienceExperience building or leading teams at cloud data platforms such as Snowflake, BigQuery, Redshift, or similar systems. Direct exposure to data warehouse architecture, analytics optimization, and enterprise data management.
SQL and Data Manipulation Language DesignExperience designing or extending SQL dialects, implementing new SQL functions, or building domain-specific languages for data manipulation and analysis.
ML Ops and Model DeploymentBackground in building ML operations infrastructure, model serving platforms, or systems for managing machine learning models in production at scale.
Unstructured Data ProcessingExperience building systems that handle and process unstructured data (text, images, documents) at scale, particularly in analytics or search contexts.
Open Source LeadershipTrack record of leading or significantly contributing to open-source projects, particularly in data systems, databases, or machine learning infrastructure domains.
Enterprise SaaS Product ExperienceBackground building and scaling B2B SaaS products with complex technical architectures serving large enterprise customers with strict reliability and performance requirements.
Strategic M&A IntegrationExperience integrating technologies or teams acquired through M&A, particularly in scaling and consolidating engineering organizations while maintaining product innovation.
AI-Native Organization BuildingExperience building teams and organizations that adopt AI-native approaches to problem-solving, decision-making, and product development with experimental mindsets.
Compensation & benefits
Salary
USD 304,000 – 437,000 (annual)
Stock options
Available
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Snowflake is an American cloud computing company offering data warehousing and analytics platforms.
Bozeman, Montana, United StatesFounded 2012snowflake.com
Tech Stack
Languages
SQLPythonC++JavaScala
Frameworks
Apache SparkTensorFlowPyTorchLangChainRay
Databases
SnowflakePostgreSQLBigQueryDelta LakeVector Databases
Tools
KubernetesTerraformGit and GitHubJira and ConfluenceDataDog or New Relic
Other
Cloud Platforms (AWS, Azure, GCP)Machine Learning Operations (MLOps)Data Engineering Best PracticesEnterprise Security and ComplianceAI Ethics and Responsible AI
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