Technical Lead Manager - Frontend, Cortex AI

Snowflake4 months ago

Location

US-CA-Menlo Park

Type

Full Time

Salary

USD 200,000 – 287,500

Level

Manager

Role

Engineering Manager

Posted

Mar 2, 2026

Full TimeManager

The role

Summary

Lead a high-impact frontend engineering team building AI-powered user experiences at Snowflake's Cortex AI division. As Technical Lead Manager, you'll drive technical strategy, architect scalable AI/ML-powered interfaces for enterprise data interaction, and mentor a team of frontend engineers while maintaining hands-on involvement in complex system design. This role combines deep technical leadership with people management, requiring 9+ years of large-scale system design experience and 3+ years of team leadership in mission-critical frontend environments.

What you'll do

Own Technical Strategy and Execution: Drive the complete frontend product lifecycle from initial conception through detailed system design to production deployment. Establish technical direction for the AI Frontend team, making critical architectural decisions that balance scalability, performance, and user experience. Ensure projects are executed with high quality and shipped on time with measurable impact on Snowflake's enterprise customers.

Provide Technical Oversight and Architecture Leadership: Actively participate in design reviews, system architecture discussions, and complex frontend implementation challenges. Ensure the team builds scalable, reliable systems that handle high-concurrency scenarios and deliver exceptional UX. Set engineering standards and best practices for AI/ML-powered frontend development across the team, maintaining oversight without creating bottlenecks.

Serve as Subject Matter Expert in AI/ML Frontend Development: Demonstrate deep expertise in building LLM-powered and AI-native user interfaces. Establish yourself as the go-to technical authority for complex frontend challenges, code reviews, and architectural decisions. Set the bar for engineering excellence and continuously evolve the team's capabilities in emerging AI/ML frontend patterns and enterprise UX design.

Collaborate Across Product, Design, and Engineering: Work closely with product managers and UX/UI designers to translate user needs and business objectives into concrete technical roadmaps. Partner with backend and platform teams to ensure seamless integration and drive alignment on the broader AI applications platform. Advocate for frontend concerns during cross-functional planning and influence product direction based on technical insights.

Mentor, Coach, and Build a Strong Team: Develop engineers through mentorship on complex technical challenges and career growth opportunities. Lead proactive and deliberate hiring to build a strong, diverse team with complementary skills. Create a culture of learning and technical excellence while supporting team members through challenging projects and professional development milestones.

Define Team Plans and Accountability: Establish clear team deliverables and roadmaps aligned with Snowflake's business objectives. Maintain accountability for the frontend platform's availability, performance, and maintainability across the full AI application lifecycle. Monitor key metrics, troubleshoot production issues, and continuously optimize team velocity while maintaining quality standards.

Drive Engineering Process Improvement: Lead the evolution of engineering processes, developer tooling, and technical standards with a focus on velocity, code quality, and developer experience. Implement best practices for testing, deployment, and monitoring. Champion the adoption of modern development methodologies and AI-native tooling to accelerate team productivity.

Champion AI-Native Development Practices: Model and scale the use of AI coding assistants such as Claude Code, Cursor, and Codex as core components of the team's development workflow. Demonstrate how AI can enhance developer productivity and code quality. Guide the team in treating AI as a high-trust collaborator rather than a simple autocomplete tool, establishing best practices for AI-augmented development.

What we look for

Technical

JavaScript and TypeScript ProficiencyDeep hands-on expertise in JavaScript/TypeScript with ability to architect and implement complex frontend systems. Strong understanding of advanced language features, async patterns, and performance optimization techniques. Comfortable diving into implementation details while designing scalable abstractions.

React Ecosystem MasteryProduction-level proficiency with React and its ecosystem. Experience with state management patterns, hooks architecture, performance optimization, and building component libraries. Understanding of modern React patterns for building maintainable, scalable applications.

System Design and ArchitectureStrong foundation in software engineering principles including design patterns, data structures, algorithms, and system design. Ability to architect large-scale frontend systems that handle high-concurrency, low-latency requirements. Experience designing systems for scalability, reliability, and maintainability.

Additional Programming LanguageProficiency in at least one additional language such as Python, Go, or Java. Demonstrates broad programming capabilities and ability to understand backend systems and their interaction with frontend layers.

AI/ML Application DevelopmentExperience designing and building user experiences that leverage LLM models and AI capabilities. Understanding of AI/ML concepts relevant to frontend development, including prompt engineering, inference optimization, and handling AI model outputs in user interfaces.

Cloud Platform ExperienceWorking knowledge of cloud environments such as AWS, Azure, or GCP. Experience with cloud-native architectures, serverless functions, and cloud-based deployment pipelines relevant to frontend applications.

Education

Computer Science or Engineering DegreeBS, MS, or PhD in Computer Science, Engineering, or a related field. Demonstrates foundational computer science knowledge and formal training in software engineering principles.

Equivalent Professional ExperienceEquivalent professional experience in software engineering or related fields. Extensive track record in building and shipping production systems can substitute for formal degree.

Experience

Large-Scale System Design9+ years designing and building large-scale, user-facing systems in production. Demonstrated track record of shipping high-quality products used by thousands or millions of users. Experience navigating complex technical challenges, performance optimization, and reliability considerations at scale.

Team Leadership and Management3+ years managing and leading engineering teams delivering mission-critical, high-concurrency, low-latency user interfaces. Proven ability to hire, mentor, and grow engineers. Track record of building high-performing teams with strong technical culture and psychological safety.

Product Execution LeadershipDemonstrated ability to translate product requirements into technical specifications and lead engineering execution from concept to launch. Experience owning end-to-end product delivery, managing trade-offs, and shipping features that customers love.

Enterprise and Data ProductsExperience building data analytics, business intelligence, or conversational AI products for enterprise customers. Understanding of enterprise customer needs, compliance considerations, and the demands of B2B data products.

Skills

Required skills

JavaScript/TypeScriptExpert-level proficiency with strong ability to architect complex frontend systems

ReactProduction expertise with modern React patterns, hooks, state management, and performance optimization

System DesignAbility to design scalable, reliable systems with understanding of performance, reliability, and maintainability

Team LeadershipProven ability to hire, mentor, and grow high-performing engineering teams

Product-Engineering CollaborationStrong communication skills translating product requirements into technical specifications

Frontend ArchitectureExperience architecting large-scale frontend applications and establishing technical standards

Nice to have

LLM Application DevelopmentExperience shipping LLM-powered applications through work, open source, or personal projects

AI Coding AssistantsActive daily use of AI coding assistants treating AI as a high-trust collaborator, not just autocomplete

Cloud PlatformsExperience with AWS, Azure, or GCP cloud environments and cloud-native architectures

Data Products ExpertiseBackground building data analytics, BI, or conversational AI products for enterprise users

Backend Services KnowledgeFamiliarity with backend services and APIs powering AI/ML inference and data retrieval at scale

Python, Go, or JavaAdditional programming language proficiency for cross-functional collaboration

Compensation & benefits

Salary

USD 200,000 – 287,500 (annual)

Stock options

Available

Benefits

Equity and Stock Options

Participate in Snowflake's growth as a publicly traded company with competitive equity packages for leadership roles

Comprehensive Health Coverage

Medical, dental, and vision insurance with employer contributions supporting your and your family's wellness

Retirement Planning

401(k) plans with company matching to support long-term financial security

Flexible Work Environment

Remote-friendly work arrangements supporting work-life balance and flexibility

Professional Development

Learning budgets, conference attendance, and continuous education opportunities to stay current with emerging technologies

Generous Time Off

Competitive vacation policies, parental leave, and wellness days supporting personal well-being

Innovation and Impact

Opportunity to shape Snowflake's AI strategy and work on products transforming enterprise data interaction

Interview process

1
Initial Screening Call — Phone conversation with recruiter to discuss background, motivations, and alignment with the Technical Lead Manager role. Focus on career progression and experience leading frontend teams.
2
Technical Leadership Interview — Deep-dive conversation with hiring manager covering your approach to technical strategy, team building, and hands-on technical contributions. Expect discussions about system design decisions, mentoring philosophy, and navigating trade-offs between technical excellence and business velocity.
3
Frontend Architecture Assessment — Technical interview evaluating your expertise in large-scale frontend architecture, JavaScript/TypeScript proficiency, and React ecosystem knowledge. May involve system design discussions or code review scenarios focused on real-world challenges Snowflake's frontend teams face.
4
AI/ML Frontend Deep Dive — Specialized interview exploring your experience building LLM-powered applications, familiarity with AI coding assistants, and understanding of how to architect frontends for AI-native experiences. Discussion of real projects or examples demonstrating AI-powered UX thinking.
5
Cross-Functional Collaboration Interview — Conversation with product or design partners to assess your ability to collaborate effectively across functions. Discuss how you translate product requirements into technical roadmaps and handle prioritization challenges between engineering excellence and feature velocity.
6
Leadership and Culture Fit Interview — Conversation with senior leadership or executive team members focusing on your leadership philosophy, team culture approach, and alignment with Snowflake's values around AI-native thinking, low-ego collaboration, and experimental mindset.
7
Final Round Discussion — Executive round with department leadership to discuss your vision for the AI Frontend team, questions about Snowflake's direction, and mutual assessment of long-term fit and growth potential at the company.