logo inner

Enterprise Product Manager

TectonCa / New York, New York, United StatesRemote, Onsite
This job is no longer open
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


Tecton’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

Apply for this job

This job is no longer open

Life at Tecton

Founded by the team that created the Uber Michelangelo platform, Tecton provides an enterprise-ready feature store to make world-class machine learning accessible to every company. Machine learning creates new opportunities to generate more value than ever before from data. Companies can now build ML-driven applications to automate decisions at machine speed, deliver magical customer experiences, and re-invent business processes. But ML models will only ever be as good as the data that is fed to them. Today, it's incredibly hard to build and manage ML data. Most companies don't have access to the advanced ML data infrastructure that is used by the internet giants. So ML teams spend the majority of their time building custom features and bespoke data pipelines, and most models never make it to production. We believe that companies need a new kind of data platform built for the unique requirements of ML. Our goal is to enable ML teams to build great features, serve them to production quickly and reliably, and do it at scale. By getting the data layer for ML right, companies can get better models to production faster to drive real business outcomes.
Thrive Here & What We Value1. Diversity and equal opportunity employment2. Comprehensive benefits package (medical, dental, vision, life insurance, 401(k), flexible paid time off, eight paid holidays annually, sick leave, FMLA-compliant leaves)3. Global team with offices in San Francisco and New York City4. Venture capital funding from Sequoia Capital, Andreessen Horowitz, Kleiner Perkins, Snowflake, Databricks5. Emphasis on innovation and technical expertise
Your tracker settings

We use cookies and similar methods to recognize visitors and remember their preferences. We also use them to measure ad campaign effectiveness, target ads and analyze site traffic. To learn more about these methods, including how to disable them, view our Cookie Policy or Privacy Policy.

By tapping `Accept`, you consent to the use of these methods by us and third parties. You can always change your tracker preferences by visiting our Cookie Policy.

logo innerThatStartupJob
Discover the best startup and their job positions, all in one place.
Copyright © 2024