Data Product Engineer
NxT Level
Data Product Engineer
Location: San Francisco / In-person preferred
Employment Type: Full-time
Experience: 58 years
Focus: Data Products AI Agents Insurance Data Pipelines Evaluation Systems
About Our Client
Our client is building an AI-native platform for insurance profit and loss teams.
The company is focused on helping insurance organizations make better faster decisions by turning fragmented external data into trusted signals that AI agents can understand reason over and act on.
Backed by Lightspeed and Valor our client has raised $10M in seed funding and is building foundational technology for one of the largest industries in the world. This is an opportunity to join as a founding engineer and help shape the data layer of the platform from the ground up.
About the Role
Our client is hiring a Data Product Engineer to build the data infrastructure and product layer that powers their AI platform.
This role sits at the intersection of data engineering product engineering customer discovery and AI systems. Youll work directly with customers to identify high-value data use cases determine which external data sources matter most and own the full path from raw source data to production-ready signals.
The ideal candidate is someone who can build reliable data pipelines think deeply about data quality expose data through intuitive product surfaces and create evaluation systems that ensure agents can produce accurate and trusted answers.
What Youll Do
Work directly with customers to identify common high-value insurance data use cases
Determine which external data sources should be brought into the platform
Build and maintain end-to-end data pipelines across ingestion extraction synthesis and transformation
Turn raw legal financial company and insurance-related records into trusted production signals
Expose data through product surfaces that are easy for AI agents and users to consume
Build systems that help agents answer questions accurately using reliable data
Create and maintain evaluation harnesses to measure data quality and agent reliability
Partner closely with founders customers and technical teams to shape product direction
Own core pieces of the data layer from scratch as an early engineering hire
Build scalable foundations for a platform serving insurance teams in a massive market
What Were Looking For
58 years of experience in data engineering product engineering or software engineering
Strong experience building production data pipelines and data products
Ability to work directly with customers and translate business problems into technical systems
Strong understanding of data ingestion extraction transformation synthesis and quality
Experience working with messy external data sources
Strong product instincts and the ability to build data systems that are useful to end users
Experience building systems that support AI agents LLMs retrieval or automated workflows
Comfort creating evaluation frameworks for data quality accuracy and reliability
Strong ownership mindset and ability to operate in an early-stage startup environment
Clear communication skills and comfort working across customers founders and engineering
Bonus Experience
Experience in insurance fintech financial services legal data compliance or regulated industries
Experience building AI-native products or agentic data workflows
Experience with document extraction entity resolution data enrichment or external data integrations
Experience building evaluation harnesses for LLMs agents or data pipelines
Experience as a founding engineer or early engineer at a seed-stage startup
Experience turning ambiguous customer problems into scalable product infrastructure
Why This Opportunity
Join as a founding engineer at a $10M seed-stage company
Build the foundational data layer for an AI-native insurance platform
Work directly with customers to identify and solve high-value data problems
Own the full path from raw external data to trusted agent-ready signals
Partner closely with the founding team and shape the technical direction early
Build in a $6T industry with massive opportunity for AI-driven transformation
Work on hard problems across data quality AI reliability product surfaces and agent trust
Required Experience:
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