Software Engineer, Data Mining
About NationGraph
NationGraph is building the data and intelligence layer for the public sector.
More than 110,000 state and local government agencies across the U.S. independently publish information about:
That information is fragmented across millions of websites, documents, databases, procurement systems, meeting records, and public records.
NationGraph turns that information into structured, connected, actionable intelligence for businesses selling to government.
Founded in 2024, NationGraph is dedicated to making uncommon knowledge common, because public data should actually be public.
The Role
We’re looking for a Software Engineer, Data Mining to own one of the most important technical problems at NationGraph: building the systems that acquire public-sector information from across the internet at massive scale.
Our goal is to operate hundreds of thousands, and eventually millions, of scrapers covering every level of government across the U.S. and Canada, and eventually worldwide.
This is not a role focused on manually building individual scrapers. You’ll own the infrastructure, abstractions, and automation that allow us to create, deploy, monitor, and maintain an enormous fleet of scrapers reliably.
You’ll work across:
Web crawling and scraping
Browser automation
Distributed systems
Data extraction
Infrastructure and orchestration
LLMs and agents
Monitoring and observability
What You’ll Do
Own our scraping infrastructure end-to-end
Build systems for creating, deploying, scheduling, monitoring, and maintaining hundreds of thousands of scrapers.
Design abstractions that allow us to scale toward millions of sources without scaling engineering effort linearly.
Build for the messy internet
Work across government websites, APIs, procurement systems, PDFs, spreadsheets, meeting records, and legacy systems.
Handle changing websites, undocumented APIs, rate limits, broken sources, and countless edge cases.
Make scraping a distributed systems problem
Build for orchestration, concurrency, retries, backfills, change detection, observability, cost management, and failure recovery.
Ensure we know when sources break, data disappears, or extraction silently becomes incorrect.
Use AI to rethink scraping
Work with our ML Research team to use LLMs and agents to:
Build systems that get better with scale
Expand our coverage globally
You Might Be a Good Fit If
You’re an unusually strong engineer who enjoys figuring out how things work.
You’ve built production web crawlers, scraping systems, browser automation, or large-scale external data pipelines.
You’re strong in Python, Go, TypeScript, or another backend/systems language.
You understand the realities of scraping modern websites, including:
You understand distributed systems, including:
Orchestration
Queues and concurrency
Idempotency
Retries
Backfills
Observability
Failure recovery
You care deeply about data quality, correctness, and reliability.
You’re excited about using LLMs and agents to automate traditionally manual scraping work.
You naturally think about leverage: not how to scrape one website, but how to build a system capable of scraping the next 10,000.
You thrive in ambiguity and would rather build the system than be handed one.
We’re particularly interested in backgrounds spanning:
None of these are requirements.
Our Engineering Stack
Backend: Python, Go, PostgreSQL
Infrastructure: Redis, Docker, Kubernetes
Frontend: React, TypeScript
AI / ML: LLMs, agents
Our stack will evolve, you’ll help decide how.
Why NationGraph
Own a foundational problem
A large part of this architecture still needs to be invented.
You’ll have significant ownership over how NationGraph discovers, acquires, represents, and serves public-sector information.
Work on a genuinely hard data problem
There is no single API for American government.
There are tens of thousands of institutions, millions of sources, inconsistent schemas, and enormous amounts of information buried in systems never designed for machines.
Build a real data moat
We believe a major long-term advantage in applied AI will come from proprietary context and data.
Government contains enormous amounts of valuable information that is technically public but practically inaccessible.
Your job is to change that.
Work with exceptional people
You’ll work closely with the CEO, CTO, and a small engineering and research team.
The team has backgrounds spanning high-scale infrastructure, quantitative finance, AI, and startups.
Have real ownership
If the idea of building the data infrastructure to map and understand how government works sounds exciting, we’d love to talk.
