InQuery is a fully-managed lake house engine that helps businesses scale their analytical workloads for a fraction of the cost.
📍 New York City, In-Person/Hybrid | 💼 Full-time | 🛠Early-stage startup
About Us
At InQuery, we’re building AI-powered software that helps legal and insurance professionals make sense of overwhelming stacks of medical records. Our platform automatically organizes, deduplicates, and summarizes documents so claims adjusters, attorneys, and medical experts can get to the facts faster and with fewer errors.
We work across some of the most complex and high-stakes areas of insurance and law—like workers’ compensation, liability and mass tort, personal injury, and disability/Medicare set-asides—where accurate understanding of medical records directly impacts costs, outcomes, and people’s lives.
We’re a small but ambitious team of engineers from Stanford and MIT, backed by Y Combinator, General Catalyst, and DRW VC. Today we process over 100,000 pages of records every month, and we’re scaling rapidly toward millions.
The Role
As a Founding Engineer, you’ll work directly with the founders on everything from backend systems to frontend UX. You’ll help us take real customer problems and quickly design, build, and ship solutions. Some days you’ll be polishing a UI for attorneys, paralegals, and nurses, other days you’ll be designing schemas for medical records at scale, or even joining customer calls to understand their workflow deeply. We have plenty of work across net new features, backend scalability, and ML/AI Agent research.
This is a role for someone who wants ownership, variety, and velocity — and who’s excited to help scale a product from thousands to millions of pages per month.
👉 This role is perfect for someone who’s excited about startups and wants to learn how to build a business from 1 -> 100 (and new product features from 0 -> 1).
Every medical-legal case runs on records. A workplace accident, a car crash, a surgery — each one generates documentation that grows from a single note into thousands of pages spanning ER visits, specialists, physical therapy, diagnostics, billing, and often years of prior history. These records touch everyone: adjusters, attorneys, physicians, case managers, vendors, and regulators. They form the backbone of medical-legal work.
The problem is that the system hasn’t kept up with the scale or complexity. Records arrive as PDFs, scans, handwritten notes, and exports from dozens of systems. They’re duplicated, out of order, or commingled across accidents and even patients. Reviewing them is almost entirely manual — adjusters copy-paste into spreadsheets, attorneys build timelines by hand, and nurses or paralegals spend 10–15 hours organizing a single file. It’s slow, expensive, and error-prone.
The consequences are real: missed details affect case outcomes, duplicated services inflate costs, and bottlenecks limit how many cases a team can handle. At scale, this inefficiency means fewer cases resolved, slower settlements, higher costs, and overworked staff.
At InQuery, we believe this work doesn’t have to be this painful. We’re building technology that takes unstructured records and makes them structured, searchable, and usable. Our system retrieves, segments, organizes, and augments records; extracts the structured data professionals actually need (providers, diagnoses, procedures, codes); and produces outputs like chronologies and timelines that teams can trust. The goal isn’t to replace human judgment — it’s to give experts the bandwidth to apply their skills where it matters most.
We’re already processing over 100,000 pages a month. By the end of this year, we need to scale to 1 million, and by 2026, 10 million. If you care about building reliable systems that solve messy, real-world problems — and about helping professionals in law, insurance, and healthcare do their jobs better — this is the place to do it.
Technical Description for Job Description Frontend & Backend Development: Programming Languages: TypeScript and Node.js Frameworks: Express, NestJS, or similar frameworks Infrastructure: Hosted on AWS (Amazon Web Services) Deployment and Scaling: Elastic Beanstalk, ECS, Lambda, etc. Security and Networking: IAM roles, VPCs, Security Groups, etc. Monitoring and Logging: CloudWatch, X-Ray, etc. Data Management: Databases: MySQL, PostgreSQL Data Warehousing/ETL: Connected to Trino, Apache Spark Backend/Research: Data Analysis and Machine Learning: Python (Pandas, NumPy, Scikit-Learn, etc.) API Integration: FastAPI, Flask, etc.
fulltimeNew York, NY, USFull stack$120K - $200K0.50% - 1.00%Any (new grads ok)
fulltimeNew York, NY, USFull stack$140K - $220K0.50% - 1.50%3+ years