United States onlyTecton’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 RoleTecton’s Ideal Customer Profile are Enterprise companies that want to standardize on a single feature platform across multiple ML & AI products. Such teams require collaboration, security, governance, compliance, lifecycle management, and system-of-record features to successfully use Tecton across a large number of engineers and data scientists.
By taking on this role, you will be responsible for making sure Tecton has the security, privacy, and governance capabilities needed to succeed in the enterprise. You will directly contribute significant revenue opportunities by unlocking new enterprise deals and enabling existing customers to expand by bringing more teams onto a shared platform.
In the long run, you’ll build the foundational moat that enables Tecton to quickly expand in the ML & AI stack while leveraging core collaboration infrastructure.
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
- 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
- Uplevel our internal product processes for working with our largest accounts
Qualifications
- 5+ years of Product, Engineering, or similar technical roles
- 2+ years of experience building for Enterprise customers
- 2+ years experience in Developer or Data/ML infrastructure products
- Comfortable interfacing directly with high-value accounts
Nice-to-have
- Experience working in a startup environment
- Experience working on Applied ML products
- Experience working with Security teams or requirements
