Forward Deployed Data Engineer

Lunon; Oregon; Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Remote in US

Collaborative team

AI-driven projects

Job summary

Lunon is hiring a Forward Deployed Data Engineer to build the foundation for AI systems. You will ensure data is complete, traceable, and trusted, collaborating with a Forward Deployed AI Engineer on an ERP-focused project.

You will own data ingestion, quality controls, and dataset curation for model evaluation, operating these systems at enterprise scale and delivering enduring infra for Lunon’s team.

Qualifications

• Built and operated production data pipelines.
• Strong Python and SQL skills; experience with a data warehouse or lakehouse.
• Experience preparing data for ML/LLM systems.
• Familiarity with data quality and lineage controls.
• Ability to work with AI coding tools daily.

Responsibilities

• Extract data from ERP, CRM, and accounting systems and design pipelines.
• Establish quality and lineage so figures can be traced to sources.
• Curate training and evaluation datasets for models.
• Run systems in production at enterprise scale and ensure reliability.
• Leave behind infrastructure for the internal team to operate.

Skills

Python

SQL

Data pipelines

Production systems

Data quality

Tools

Snowflake

BigQuery

Databricks

Postgres

Job description

ABOUT LUNON

The companies that lead the next decade won't adopt AI, they'll be rebuilt around it. Lunon treats strategy and software as one discipline, shaping the systems that let ambitious companies outthink their markets and outpace their competitors. Most advice about AI ends as a recommendation that someone else has to carry out. At Lunon, the people who decide what should change are the people who build it, so an insight becomes capability rather than a slide. We are backed by General Catalyst, and our open-source research system ranks first on DeepResearch Bench. We're a small team and intend to stay that way. Everyone here owns their work from the first conversation to production, adopts the newest models as they land, and holds an exacting standard for craft. If you want your work to change how a company operates, not just inform it, we'd like to meet you.

ABOUT THE ROLE

As a Forward Deployed Data Engineer, you will own the foundation our AI systems stand on. A model is only as good as the data it learns from and is measured against; your work makes that data complete, traceable, and trusted. You will work alongside a Forward Deployed AI Engineer, who owns the models. Your first project: helping an ERP company make its product AI-native.

RESPONSIBILITIES

• Extract data from ERP, CRM, and accounting systems and design the pipelines that keep it flowing: ingestion, transformation, and storage
• Establish quality and lineage controls so every figure can be traced to its source
• Curate the training and evaluation datasets our models learn from and are judged by
• Run these systems in production at enterprise scale and own their reliability
• Leave behind infrastructure the company's own team can operate and extend

YOU MAY BE A FIT IF

• You have built and operated production data pipelines, and kept them running when they broke
• You write excellent Python and SQL, and have worked with a warehouse or lakehouse such as Snowflake, BigQuery, Databricks, or Postgres
• You can bring order to data from systems you did not design
• You have prepared data for an ML or LLM system: training sets, evaluation sets, or retrieval
• You work with AI coding tools every day and judge the result by the system it produces

STRONG CANDIDATES MAY ALSO

• Have built on or integrated with an ERP, CRM, or accounting system
• Have built data quality or lineage tooling that others depended on
• Have done consulting or forward-deployed work, and know how to earn trust inside a company that isn't yours

LOCATION

Remote within the US. Lunon is headquartered in New York City.

HOW WE HIRE

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