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Last checked Nov 1, 2026.

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:
• JavaScript rendering
• Sessions and cookies
• Rate limits
• Proxies
• Authentication
• Changing schemas and websites
• 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

• Alternative data
• Quantitative research infrastructure
• Search and crawling
• AI data infrastructure
• Knowledge graphs
• Large-scale document processing
• Data aggregation

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
• We move quickly.
• We operate with very little bureaucracy.
• Engineers have significant ownership over technical decisions and product outcomes.

If the idea of building the data infrastructure to map and understand how government works sounds exciting, we’d love to talk.