About NationGraph NationGraph is making public sector data accessible and actionable for businesses selling to cities, counties, state agencies, schools, and special districts. NationGraph's data and intelligence engine provides buying signals derived from millions of public sector sources. Founded in 2024, NationGraph is dedicated to making uncommon knowledge common, because public data should actually be public. Learn more at nationgraph.com
You’ll Join A Team That: Has successfully built, scaled, and sold companies in the past.
Built software infrastructure processing billions of dollars in transactions.
Is backed by world-class VCs and operating partners who've invested in, and built, iconic companies.
About The Role: Own the systems behind NationGraph's unique differentiated asset: the data acquisition platform that collects public information/records at scale, (purchase orders, contracts, various procurement documents) from 100k+ government entities across the country. No one else has solved this government data problem. You'll be one of the people who helps change that.
This is real data engineering, not dashboard plumbing. You'll build high-volume interaction and ingestion pipelines with retries, dead-letter handling, checkpointing, and resumability; turn messy government documents (PDFs, spreadsheets, scans, portals) into clean structured data; and keep it flowing into the product reliably.
Build with AI at the core: LLM-driven document extraction, classification, and form processing at scale are already in production here, but there's a wide-open opportunity to make them more modular, rigorous, cheaper, and faster.
Also design some human-in-the-loop systems. Some pipelines pair automation with a dedicated operations team; you'll contribute to the internal platform they work in every day,



complying with access controls, audit logging, and workflow tooling meeting SOC 2 requirements.
Own problems end to end in a small, senior team. You'll take a goal like "automate records requests through web portals" from research to design doc to production, and you'll see your work show up directly in customer accounts and revenue.
Every decision you make materially changes the trajectory of the company.
What you’ll need: 5+ years building production backend systems
Strong TypeScript/Node - the platform is a TypeScript monorepo (API + React frontend). You write well-structured, typed services and know your way around async execution, streams, and queues
Pipeline engineering depth - idempotent processing, retries with backoff, dead-letter handling and recovery, checkpoint/resume for long-running jobs, backpressure, graceful degradation when downstream services fail
Solid PostgreSQL - schema design, secure migrations on live tables, indexing strategies, query optimization, and comfort operating a database that other teams and the product depend on
Document processing at scale - extracting reliable structured data from large volumes of inconsistent files (PDFs, spreadsheets, scans), with deduplication and edge-case handling
LLM integration - calling model APIs at scale for extraction and classification, managing rate limits and cost across providers, structuring prompts and outputs so they're testable




Third-party API fluency - webhooks, pagination, rate limits, and the patience to build robust clients around finicky or poorly documented APIs
Operational ownership - you instrument what you ship, notice when a pipeline degrades before anyone flags it, and fix root causes rather than restarting jobs
Independence - you can take a fuzzy operational problem, write the design doc, break it into tickets, and ship it end-to-end
Nice to have: Browser automation and scraping at scale - Playwright/Puppeteer, anti-fragile selectors, session management, structured crawling
Email infrastructure - deliverability, SPF/DKIM/DMARC, threading and reply-matching, inbox provider APIs
Building internal tools for operations teams - workflow software, queue-based work assignment, role-based access control, audit trails
Python and/or Go
Workflow orchestration - Airflow or similar
S3/object-storage-centric data architectures
OCR and document AI beyond LLM calls
Compliance-aware engineering - SOC 2, least-privilege access, action traceability
Experience with government, civic, or public-records data (Public records familiarity is a genuine plus)
Our data ops stack: Platform: TypeScript/Node monorepo, React frontend, Zod, strict ESLint
Data: PostgreSQL, S3 object storage
Tooling: Linear, Microservices, an AI-heavy development workflow
Other: Python, Go, PostgreSQL, Redis, Docker, Kubernetes, AWS
What You’ll Get From Us: Founder-Level Exposure. Work closely with the CEO/CTO on all aspects of the business.
A zero bureaucracy environment. We believe in moving extremely fast and making bold decisions without red tape.
We believe in working with outstanding people with a diversity of thought, an eagerness to learn,

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📌 Senior Software Engineer, Data Engineering (Ontario)
🏢 PVH (Tommy Hilfiger/Calvin Klein)
📍 Ontario