Founding Data Engineer
AI summary of the role
Founding data engineer at Percepta, General Catalyst's AI transformation studio, to build data pipelines, models, and tooling that turn messy enterprise data into AI-ready assets.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Build end-to-end pipelines and models that turn fragmented, messy enterprise data into high-leverage, AI-ready assets
- Structure and normalize noisy datasets — defining the data packs and ontology that AI engineers build on top of
- Build internal product and tooling that makes data work faster and repeatable across customers
- Work directly with operators and product/AI engineers to turn high-value use cases into production data workflows
What you’ll bring
- Strong experience in some combination of Data Science, Data Engineering, Machine Learning
- Product instinct for building tooling that makes data work easier, not just doing the work
- Intuition for what modern AI/ML and LLM systems need from data (features, retrieval, context, embeddings)
- High ownership and strong communication — comfortable embedded directly with customer teams
Technologies
data engineering · data science · machine learning · LLM · embeddings · retrieval · Databricks · agentic workflows · data pipelines · ontology
About Percepta
General Catalyst's in-house AI transformation studio deploying engineers, researchers, and PMs directly into enterprises to build agentic workflows via Mosaic toolkit.
Private Late
Source and classification
Internal deployment & tooling · Evidence for this classification:
one of the founding members of Percepta's data team — a role that lives across the full spectrum from data engineering to data science to ML engineering. You won't be boxed into one of those; the best person here has a center of gravity in one and real range across the others. The job has two halves, and you'll do both: Be the data person. Build the pipelines, models, analysis, "data packs," and ontology that turn messy enterprise data into something AI can actually use — and do it fast, inside real customer environments. Build the product around that. Build the tooling, abstractions, and increasingly agentic/automated systems that make the first half faster and compounding across every customer we work with. This is where you set the taste and help form our strategy for how Percepta does data — not as a one-off, but as something that gets better every time we do it. As a founding
More from the job description
Who We Are Percepta’s mission is to transform critical institutions with applied AI. We care that industries that power the world (e.g. healthcare, manufacturing, energy) benefit from frontier technology. To make that happen, we embed with industry-leading customers to drive AI transformation. We bring together: Forward-deployed expertise in engineering, product, and research Mosaic, our in-house toolkit for rapidly deploying agentic workflows Strategic partnerships with Anthropic, McKinsey, AWS, companies within the General Catalyst portfolio, and more Our team is a quickly growing group of Applied AI Engineers, Embedded Product Managers and Researchers motivated by diffusing the promise of AI into improvements we can feel in our day to day lives. Percepta is a direct partnership with General Catalyst, a global transformation and investment company. About The Role We're hiring one of the founding members of Percepta's data team — a role that lives across the full spectrum from data engineering to data science to ML engineering. You won't be boxed into one of those; the best person here has a center of gravity in one and real range across the others. The job has two halves, and you'll do both: Be the data person. Build the pipelines, models, analysis, "data packs," and ontology that turn messy enterprise data into something AI can actually use — and do it fast, insid [... source excerpt omitted ...] ironments. Build the product around that. Build the tooling, abstractions, and increasingly agentic/automated systems that make the first half faster and compounding across every customer we work with. This is where you set the taste and help form our strategy for how Percepta does data — not as a one-off, but as something that gets better every time we do it. As a founding hire, you're not inheriting a playbook — you're writing it. What You'll Do Build end-to-end pipelines and models that turn fragmented, messy enterprise data into high-leverage, AI-ready assets Structure and normalize noisy datasets — defining the data packs and ontology that our AI engineers build on top [... source excerpt omitted ...] and repeatable across customers, so each engagement compounds rather than starts from zero Work directly with operators and product/AI engineers to turn high-value use cases into production data workflows Form strong technical opinions on data models, storage, orchestration, and infra tradeoffs — and make the calls What We're Looking For You might come from any point on the spectrum — a strong data engineer; a software engineer who's done real data work; someone who's done data science and software; or an ML engineer who now wants to build more. What's common: you can build in ambiguity, you form opinions and ship, and you care about building leverage, not just outputs. Strong
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