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.

As a staff-level engineer building Tecton platform team, you’ll play a critical role in architecting, designing, and scaling our Tecton’s platform-level building blocks for building the next generation of accessible ML infrastructure.

As part of this team, you will be working in one or more of the following areas to build the next generation of Tecton infrastructure:

• Architecting APIs and abstractions over multiple cloud, storage, and compute platforms
• Building platforms that enable modular development and testing
• Transitioning Tecton’s control plane toward a multi-tenant architecture
• Explainability and debugging as a first-class property of every layer of the stack
• Fleet management and optimizations for hundreds (and eventually thousands) of Tecton deployments
• Partnering with Security on org-wide data privacy and security measures

• Own and lead large technical domains starting from the problem definition and technical requirements along with implementation and maintenance
• Lead multi-engineer projects of strategic importance to Tecton spanning cross-functional teams including design, product management, and other engineering teams
• Drive efforts to improve engineering practices, tooling, and processes along with mentorship for senior engineers
• Develop a deep understanding of the fundamental problems our customers face in building ML systems
• Be a generalist as needed. We’re a small, but growing engineering team and each engineer needs to be versatile
• Reinforce Tecton’s “Fast, but Focused” core value

• 7 years of experience in building product software systems
• 2 years of technical leadership experience for a group of engineers
• Experience working in large Python, Java, Kotlin, or Go codebases and running cloud-native production systems using Kubernetes, AWS, and Docker
• Experience with distributed systems, SQL, and NoSQL databases
• Bias to action and passion for delivering high-quality solutions
• Strong communication and ability to write detailed technical specifications
• Excitement about coaching and mentorship of junior engineers
• BSc, MS, or PhD in Computer Science or related fields

Tecton values diversity and is an equal opportunity employer committed to creating an inclusive environment for all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other applicable legally protected characteristics. If you would like to request any accommodations from the application through to the interview, please contact us at recruitingteam@tecton.ai.

This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.