At Tecton, we are on a mission to bring Machine Learning and AI to every customer and product interaction on the planet. We build an enterprise-grade, world-class Feature Platform – the infrastructure that powers real-time ML applications and systems in production.
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 should take this role
Tecton is the industry’s leading feature platform - used by Data Scientists and ML Engineers at ML powerhouses like Atlassian, Block, and Coinbase.
By taking on this role, you will be responsible for bringing Tecton’s existing technology foundation to our customers’ GenAI use cases. The field is evolving quickly and you’ll need to be on your toes, and deeply immersed in the GenAI space. You will expand Tecton’s offering into a versatile platform that can power diverse GenAI use cases such as hosting RAG applications, using LLMs to extract features, generating historical training data to fine tune enriched prompts, and powering agentic workflows with tools.
Separately, you will be responsible for managing Tecton’s multi-cloud offering.
You will work directly with ML Platform teams & use case teams. This will expose you to the bleeding edge of production AI applications that have immediate impact on our customers’ bottom lines. You will learn how ML is applied across use cases as varied as recommendation systems, search ranking, fraud detection, anti money laundering, price predictions, safety predictions, personalization, credit underwriting and much much more.
You will directly contribute significant revenue opportunities by unlocking new use cases for our customers.
Detailed Responsibilities
- Own the strategy and roadmap for making Tecton the best platform to power predictive ML and generative AI use cases
- Drive Tecton’s growth on GCP, our latest supported cloud offering
- Work closely with customers & engineers to launch impactful new capabilities at a rapid pace
- Partner with Product Marketing to educate the market on why Tecton is a clear choice for predictive AI and generative AI use cases
Qualifications: Must have
- 5+ years of combined SWE or Product Management experience
- 2+ years of Product Management experience
- 6+ months of hands-on experience building GenAI applications
- 2+ years of experience building either
- Comfortable interfacing directly with enterprises
-- user experiences for technical products that cater to ML Engineers or Data Engineers
-- OR applied ML applications
Qualifications: Nice-to-have
- Experience working in a startup environment
- 2+ years experience building product for Enterprise customers
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 [email protected].
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.
Top Skills
What We Do
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.
