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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.
Snowflake’s Feature Store is a core component of our enterprise Machine Learning Platform, enabling customers to build, manage, and serve machine learning features directly within the Snowflake AI Data Cloud. It powers both offline training and low-latency online inference, supporting batch and streaming pipelines at enterprise scale.
We are looking for a Principal Tech Lead Manager (TLM) to serve as the primary architect and technical visionary for our real-time and online serving infrastructure. This is a high-impact, deeply hands-on role designed for a technical leader who thrives on solving deep distributed systems problems while simultaneously building and managing a world-class engineering team. You will shape the long-term strategic direction of Snowflake’s ML infrastructure while remaining "in the trenches" with the code.
As the Principal TLM for the Feature Store team, you will be the technical anchor for distributed systems that power feature computation, storage, and low-latency serving. You will work at the intersection of large-scale data infrastructure and real-time ML systems, ensuring that features are computed reliably and served consistently between training and inference workflows.
This role demands exceptional technical depth and a "lead-by-example" approach. You will spend a significant portion of your time coding, conducting deep-dive code reviews, and prototyping next-generation architectures. You will also partner closely with Product, Field Engineering, and core infrastructure teams to ensure our technical roadmap aligns with mission-critical enterprise AI requirements. As a TLM, you will balance this technical excellence with the growth and management of a high-performing engineering organization.
Drive Strategic Technical Vision: Define the multi-year technical roadmap for online feature serving and real-time infrastructure, balancing immediate product needs with long-term scalability.
Be Deeply Hands-On and AI-Forward: Lead by doing. You will contribute directly to the codebase, tackle the most complex "impossible" bugs, and drive the team’s productivity by embracing and implementing AI-first development practices (LLM-assisted coding, automated agents, etc.).
Architect Distributed Systems: Shape the architecture for streaming pipelines and stateful processing systems to ensure the freshness and consistency of ML features at an enterprise scale.
Set Engineering Excellence: Establish and enforce rigorous standards for high availability, performance optimizations, observability, and reliability across the entire Feature Store systems.
Manage and Mentor Senior Talent: Directly manage and provide technical mentorship to a team of high-performing engineers (including Staff+ levels). You will be responsible for their career growth, resolving complex technical conflicts, and fostering a culture of rigorous engineering.
Own Production Integrity: Take ultimate technical and operational accountability for the performance and reliability of customer-facing features from initial design through global production rollout.
12+ years of experience building massive-scale distributed systems, data infrastructure, or backend platform services.
Proven Tech Leadership & Management: A track record of acting as a Principal Engineer or Lead Architect, with demonstrated experience in people management or formal team leadership for complex, multi-tenant cloud services.
Expert-Level Technical Depth: Deep mastery of distributed systems fundamentals, including fault tolerance, consistency models, and performance tuning for low-latency systems.
Hands-on Streaming Experience: Extensive experience with large-scale streaming systems and real-time data platforms.
ML Infrastructure Exposure: While this is a data infra role, you should have a strong understanding of feature engineering workflows and/or model serving infrastructure.
Strategic Influence: Demonstrated ability to influence technical direction across multiple teams, Field Engineering, and executive stakeholders.
Execution Mindset: A history of shipping high-impact platform products that serve global enterprises.
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee’s duty to keep customer information secure and confidential.
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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