[Hiring] Forward Deployed Data Engineer @Lunon

Role Description

Lunon is an AI-native consulting firm in New York City, backed by General Catalyst. Most companies don't need another deck about AI. They need an engineer who can walk in, understand the operation, and ship. That's what we do: we embed engineers inside the business and stay until the software runs without us.

You own the data side of an engagement:

• Get the client's data out of the systems it lives in.
• Make it trustworthy.
• Turn it into the pipelines and datasets the AI runs on.

First up: helping an ERP company make its product AI-native.

What you'll do:

• Build the pipelines that pull data out of ERP, CRM, and accounting systems and keep it moving: ingestion, processing, and storage.
• Put data quality and lineage controls in place, so anyone can trace a number back to where it came from.
• Build and manage the training and evaluation datasets the models learn from and are judged on.
• Run it in production at enterprise scale. Reliability is yours.
• Document it and hand it off so the client's team can run it on their own.

Qualifications

• Experience matters here. We judge it by what you've shipped and kept running, not by a number of years.
• You've built and run data pipelines in production, including when they broke.
• You write Python and SQL well and have worked with a warehouse or lakehouse such as Snowflake, BigQuery, Databricks, or Postgres.
• You've made sense of messy data from systems you didn't design.
• You've built data for an ML or LLM system: training sets, eval sets, or retrieval.
• You use AI coding tools every day and judge the result by the system and its output, not the language.

Requirements

• Nice to have: Apply even if none of these are true.
• You've built on or integrated with an ERP, CRM, or accounting system.
• You've built data quality or lineage tooling other people relied on.
• You've done consulting, agency, or forward-deployed work and know how to be useful in someone else's building on day two.

How we hire

• A 30-minute conversation with the team about what you've shipped and what we're building.
• A technical deep-dive on one system you owned, from the business problem to production.
• A working session on a real client problem with the team.
• References, then an offer. We aim to finish in two weeks.

Beware of recruitment fraud

All official correspondence comes from a lunon.ai email address. We will never ask you to share bank account information, cash a check, or purchase equipment as part of the hiring process.