At Tecton, we solve the complex data problem in production machine learning. Tecton’s feature platform makes it simple to activate data for smarter models and predictions. Tecton abstracts away the complex engineering to speed up innovation.

Tecton’s founders developed the first Feature Store when they created Uber’s Michelangelo ML platform, and we’re now bringing those same capabilities to every organization in the world.

Tecton is funded by Sequoia Capital, Andreessen Horowitz, and Kleiner Perkins, along with strategic investments from Snowflake and Databricks. We have a fast-growing team that’s distributed around the world, with offices in San Francisco and New York City. Our team has years of experience building and operating business-critical machine learning systems at leading tech companies like Uber, Google, Meta, Airbnb, Lyft, and Twitter.

Why You’ll Love This Role

Your job is to make Tecton the obvious choice for Enterprises with sophisticated ML & AI data needs. You’ll work closely with cutting edge ML & AI teams from organizations like Atlassian, Roblox & Progressive to define our product category and push the industry forward.

You’ll have the opportunity — and accountability — for driving the majority of Tecton’s revenue by making sure our product can land and expand in the biggest accounts.

Responsibilities

• Own the strategy and roadmap for making Tecton the best collaboration environment for large AI/ML teams
• Own the strategy and roadmap for Observability & Monitoring capabilities that make Tecton the most reliable way to run AI/ML in production
• Be the voice of the Enterprise Customer and teach the rest of our Product organization how to best meet their needs
• Partner with Product Marketing to educate the market on why Tecton is a clear choice for enterprises that are serious about AI/ML
• Partner with our security experts to keep our customers’ data safe
• Partner with Support & Technical Services to ensure we have the processes to make Enterprise customers successful

• 5 years of Product, Engineering, or similar technical roles
• 2 years experience building for Enterprise customers
• 2 years experience on Developer or Data/ML infrastructure products
• Comfortable interfacing directly with high value accounts

• Experience working in a startup environment
• Experience working on Applied ML products
• Experience working with Security teams or requirements