Scale Engineer

Director of Engineering, AI Enterprise

Engineering Manager · Director · Full Time

US-CA-Menlo ParkUSD 264k – 380kToday
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Role

What you'll do.

Lead Snowflake's AI Solutions engineering organization as Director of Engineering for AI Enterprise, managing a global team building cutting-edge generative AI and machine learning solutions using Snowflake Cortex. This executive leadership role combines hands-on technical expertise with strategic vision, requiring 12+ years of software engineering experience with at least 4 years in an Engineering Director role managing managers, plus deep expertise in LLMs, natural language processing, and enterprise-scale AI deployment.

Responsibilities

  • Build and Scale Global Engineering Organization: Recruit, mentor, and develop a high-performing, distributed engineering team across multiple geographic locations. Establish and foster a culture centered on innovation, technical ownership, and engineering excellence. Implement career development frameworks and mentorship programs that attract top talent and retain institutional knowledge within the AI Solutions engineering function.
  • Define Technical Vision and Organizational Strategy: Architect the long-term technical roadmap and organizational structure for the AI Solutions team, ensuring comprehensive alignment with Snowflake's product evolution and business objectives. Lead multi-year strategic planning initiatives that balance innovation with operational efficiency and market demands.
  • Lead AI/ML Solutions Development and Deployment: Own end-to-end design, development, and production deployment of advanced AI and machine learning solutions leveraging Snowflake Cortex, Snowflake ML, large language models, and generative AI technologies. Establish engineering best practices, quality standards, and deployment methodologies for enterprise-grade AI applications that meet Fortune 100 customer requirements.
  • Drive Enterprise Customer Engagement: Serve as senior technical authority and primary engineering liaison for strategic customer engagements, including Fortune 100 accounts. Partner directly with customers and Go-To-Market teams to translate complex business requirements into scalable technical solutions. Ensure engineering solutions deliver measurable business impact and drive customer success outcomes.
  • Strategic Business Planning and Collaboration: Provide engineering perspective and leadership during strategic planning cycles, influencing headcount allocation, budget decisions, and product roadmaps. Build strong partnerships with Product Management, Research, Sales, and Customer Success teams to ensure cohesive, integrated solutions. Champion cross-functional initiatives that accelerate product delivery and market impact.
  • Advance AI/ML Methodologies and Industry Thought Leadership: Drive continuous improvement in AI and machine learning methodologies, deployment patterns, and industry best practices across the engineering organization. Represent Snowflake's AI capabilities, innovations, and technical vision within the broader technical community through speaking engagements, publications, and industry participation.
  • Customer and Team Engagement Travel: Manage up to 25% travel commitment for in-person customer engagements, global team interactions, and strategic business development activities. Build relationships with key customers, partners, and team members across geographic regions to strengthen organizational cohesion and customer satisfaction.

Qualifications

What we look for.

Technical

  • Large Language Models and Generative AI

    Hands-on expertise with transformer-based language models, prompt engineering, and generative AI technologies. Experience integrating LLMs into production applications, managing model versioning, and optimizing inference performance and cost.

  • Machine Learning Engineering

    Deep technical knowledge of ML engineering practices including model development lifecycle, data pipelines, feature engineering, model training and evaluation, and MLOps. Experience with ML frameworks (TensorFlow, PyTorch) and ML platforms.

  • Natural Language Processing

    Technical expertise in NLP technologies, semantic understanding, embeddings, information retrieval, and text processing. Experience building NLP-powered applications for enterprise use cases.

  • Cloud Data Platforms

    Strong understanding of modern cloud data warehousing, analytics platforms, and data lakes. Familiarity with cloud infrastructure providers (AWS, GCP, Azure) and serverless architectures. Knowledge of data governance, security, and compliance in cloud environments.

  • Distributed Systems Architecture

    Deep expertise designing and operating distributed systems at scale, including microservices architectures, service communication patterns, and scalability solutions. Understanding of CAP theorem, eventual consistency, and modern distributed system trade-offs.

Education

  • Computer Science or Related Degree

    Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical discipline. Master's or PhD in Computer Science or related field preferred and valued for advanced research or technical depth.

Experience

  • Software Engineering Leadership Experience

    Minimum 12+ years of progressive software engineering experience across distributed systems, cloud platforms, and large-scale enterprise systems. Demonstrated track record of technical depth and hands-on contribution across multiple technology domains.

  • Engineering Director Experience

    Minimum 4+ years in an Engineering Director or equivalent executive leadership role with direct responsibility for managing engineering managers and scaling engineering teams. Proven experience building organizational structures, defining technical strategy, and driving execution at scale.

  • AI/ML Domain Expertise

    Deep, hands-on experience architecting and deploying AI and machine learning solutions in production environments. Proven expertise building systems leveraging large language models (LLMs), natural language processing (NLP), generative AI technologies, and modern ML frameworks. Experience with prompt engineering, model fine-tuning, RAG patterns, and AI application development.

  • Enterprise Software Delivery

    Demonstrated track record of successfully designing, building, and deploying complex software solutions for enterprise customers. Clear understanding of enterprise software challenges including security, compliance, scalability, multi-tenancy, and mission-critical requirements. Experience navigating Fortune 100 or mid-market customer needs.

  • Distributed Team Management

    Proven success scaling and managing engineering teams across multiple geographic locations and time zones. Experience establishing distributed team practices, asynchronous collaboration models, and effective communication patterns across global organizations.

Skills

Required

  • AI/ML Technical Leadership

    Demonstrated ability to lead technical teams building AI and ML solutions with hands-on understanding of model development, deployment, and optimization. Capability to mentor engineers in advanced ML concepts and make sound architectural decisions.

  • Strategic Organizational Leadership

    Executive-level experience defining organizational strategy, establishing team culture, managing multiple layers of leadership, and scaling organizations from smaller teams to large distributed engineering functions.

  • Enterprise Customer Engagement

    Strong ability to partner with enterprise customers and executive stakeholders, understand complex requirements, translate technical concepts for non-technical audiences, and ensure solutions drive measurable business outcomes.

  • Cross-functional Collaboration

    Proven experience building effective partnerships with Product Management, Sales, Customer Success, Research, and other business functions. Ability to align diverse teams toward common objectives and influence without direct authority.

  • Technical Visioning and Roadmap Planning

    Capability to articulate clear long-term technical vision and strategy, define product and engineering roadmaps, and communicate vision to both technical engineers and business stakeholders.

  • Execution and Project Management

    Strong ability to drive accountability for delivery, manage complex multi-workstream initiatives, handle budget responsibility, and deliver results in dynamic, fast-moving environments.

Preferred

  • Cortex AI Platform and Snowflake Ecosystem Experience

    Nice to have

    Hands-on experience building solutions with Snowflake Cortex, Snowflake ML, or other Snowflake features. Understanding of Snowflake's data cloud architecture and integration patterns is valuable.

  • Industry Recognition in AI/ML

    Nice to have

    Active participation in the AI/ML technical community through speaking engagements, open source contributions, published research, or thought leadership. Established credibility as an AI/ML expert.

  • Venture-Scale or Startup Experience

    Nice to have

    Experience scaling engineering organizations from early stage through significant growth phases, or background in high-growth technology environments. Comfort with ambiguity and experimental mindset in emerging domains.

  • Data Platform and Analytics Expertise

    Nice to have

    Background in data engineering, analytics, or data science platforms. Familiarity with data governance, data modeling, and analytics architectures.

  • Go-To-Market and Sales Engineering Collaboration

    Nice to have

    Experience partnering closely with Sales, Sales Engineering, and GTM teams. Understanding of enterprise software sales cycles, deal structures, and customer acquisition strategies.

  • Emerging Technology Adoption

    Nice to have

    Track record of rapidly adopting and applying emerging technologies like generative AI, agentic systems, or novel ML techniques. Experimental mindset and comfort learning new tools and approaches quickly.

Tech stack

Languages

PythonJava or ScalaSQLTypeScript/JavaScript

Frameworks

LLM Frameworks (LangChain, LlamaIndex)TensorFlow / PyTorchSnowflake CortexSnowflake MLScikit-learn / PandasVector Databases (Pinecone, Weaviate, Chroma)

Databases

SnowflakePostgreSQL / MySQLVector DatabasesData Lakes (Delta Lake, Apache Iceberg)

Tools

Jupyter Notebooks / VS CodeGit / GitHubDocker / KubernetesMLflow / Weights & BiasesSnowflake APIs and SDKsCI/CD Platforms (GitHub Actions, GitLab CI)

Other

Prompt EngineeringRAG (Retrieval Augmented Generation)Fine-tuning and Model AdaptationModel Serving and Inference OptimizationAgentic AI Systems

Compensation

Pay and benefits.

Base·USD 264,000 – 379,500

Equity·Stock options

Benefits

  • Competitive Health Insurance

    Comprehensive medical, dental, and vision coverage with employer-sponsored premiums and HSA options aligned with industry standards.

  • Retirement Planning

    401(k) retirement plan with employer matching contributions to help build long-term financial security.

  • Flexible Time Off

    Generous paid time off policy enabling work-life balance and personal wellness, typically including vacation days, sick leave, and personal days.

  • Stock Options and Equity

    Equity participation enabling employees to share in company success and long-term value creation as a publicly traded company.

  • Professional Development

    Investment in continuous learning through training programs, conference attendance, certifications, and educational resources to support career growth.

  • Inclusive Work Environment

    Commitment to diversity, equity, and inclusion with employee resource groups, mentorship programs, and inclusive policies supporting all backgrounds.

  • Flexible Work Arrangements

    Remote and hybrid work options enabling flexibility in work location and schedule for work-life integration.

  • Employee Wellness Programs

    Wellness initiatives including fitness subsidies, mental health resources, counseling services, and wellness challenges.

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.

Where Data Does More. Join the Snowflake team.

Snowflake is seeking an entrepreneurial and visionary engineering leader to build and scale our new AI Solutions team. As the Director of Engineering for AI Enterprise, you will be at the forefront of the generative AI revolution, leading a world-class engineering organization that designs and implements cutting-edge solutions on the AI Data Cloud. This is a critical, high-impact leadership role where you will partner with the world's largest companies to solve their most complex challenges and unlock transformative business value using Snowflake's powerful Cortex AI Platform.

IN THIS ROLE AT SNOWFLAKE, YOU WILL:

  • Recruit, mentor, and scale a high-performing, global engineering organization. Foster a culture of innovation, ownership, and engineering excellence.

  • Define the long-term technical vision and organizational structure for the AI Solutions team, ensuring alignment with Snowflake's product evolution and business goals.

  • Lead the technical design and development of advanced AI and machine learning solutions using Snowflake Cortex and Snowflake ML. Own the end-to-end implementation of the AI Solutions product line, from initial concept to enterprise-grade production deployments.

  • Act as the senior engineering authority in customer engagements. Partner closely with Fortune 100 customers and our Go-To-Market (GTM) teams to understand their needs and ensure our solutions drive tangible business impact.

  • Serve as the engineering voice in strategic planning cycles, influencing headcount, budget, and product roadmaps. Forge strong partnerships with Product, Research, and Sales teams to deliver cohesive and powerful solutions.

  • Drive continuous improvement in AI methodologies and best practices. Represent Snowflake's AI capabilities and vision within the broader technical community.

  • Potential for up to 25% travel to engage with customers and global teams.

WE WOULD LOVE TO HEAR FROM YOU IF YOU HAVE:

  • BS/MS/PhD in Computer Science or related majors, or equivalent experience.

  • 12+ years of experience in software engineering, with at least 4 years in an Engineering Director role with experience managing managers.

  • Deep technical expertise in the AI/ML domain, with proven, hands-on experience building and deploying solutions leveraging LLMs, natural language processing, and other generative AI technologies.

  • Strong track record of delivering complex software solutions to enterprise customers, demonstrating a clear understanding of the challenges in a large-scale enterprise environment.

  • Proven experience scaling engineering organizations, including managing teams across multiple geographic locations.

  • Exceptional ability to partner with Product, Sales, Delivery and Customer Success teams and directly with customers to achieve business outcomes.

  • Excellent communication and stakeholder management skills, with the ability to articulate a technical vision and strategy to both technical and non-technical audiences.

  • Strategic mindset combined with strong project management and execution capabilities.

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

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