Senior Software Engineer ($170K - $240K + 0 - 0.4% Equity) at Anthropic's Legal Data Partner

About the job

Job Title: Senior Software Engineer

Salary: $170K – $240K + 0 to 0.4% equity

Location: New York, NY (prefer in-person but open to remote within 5 hours of EST, with 3 to 4 week onsite twice per year) | No visa sponsorship

Company Description: Anthropic's announced legal data partner, 10x ARR in 5 months, team of 8, NYC

Job Description: Join a team of 8 that just hit 10x ARR growth in the last 5 months and was publicly announced as Anthropic's legal data partner. This company is building the largest case law dataset in existence and is the only company openly selling US case law data to AI labs and legal tech companies. Their competitors still pay $300 plus per hour lawyers to do by hand what this team is automating with code. 200 plus law firms subscribe to the platform, power users spend 30 plus hours a week on it, and some of the largest legal tech and AI startups are powered by the data on the backend. You will be employee number nine at a company that is already winning the category, with greenfield problems and real technical decisions landing on your desk from week one.

Why this role is remarkable:

Join as employee nine at Anthropic's publicly announced legal data partner, a company that hit 10x ARR in 5 months with a team of 8, at the exact moment demand from AI labs and legal tech is surging and the company has the moat to capture it

Work on genuinely novel problems that no one has solved before, automating tasks that competitors still pay $300 plus per hour lawyers to do by hand, with the interesting architectural decisions still ahead of you rather than behind you

Office sits on top of the Supreme Court building in NYC, in-person culture, tight team, high ownership, one month fully remote per year, and a hardworking environment without the burnout-pipeline energy of a typical SF startup

What you will do:

Build pipelines that augment legal documents with metadata including which decisions overrule others, which are appeals or remands, and other relational structures across hundreds of thousands of court decisions, using Python and SQL as the core stack with flexibility on infrastructure

Build and maintain systems to ensure the reliability and accuracy of hundreds of web scrapers, optimize core utilities that extract and resolve citations and determine court hierarchies, and expose core services via APIs, MCPs, and WebSockets

Benchmark and evaluate core tasks using both human and synthetic evaluation, contribute to basic to intermediate infrastructure and DevOps work, and bring a cautiously AI-native mindset with active use of modern tooling to everything you build

The ideal candidate:

2 or more years of experience as a technical generalist across the backend with bonus points for fullstack ability, from a company known for strong engineering culture or an early-stage startup where you had meaningful ownership as a founding engineer, early hire, or greenfield project lead

Strong engineering fundamentals with stack loyalty being less important than genuine ownership ability, proficiency in Python and SQL, comfort standing up your own projects on your preferred infrastructure end to end, and demonstrated interest in statistics, ML, or AI

Active GitHub, side projects or unusual pursuits that demonstrate real agency outside of work, not a pure researcher or academic without sustained hands-on engineering, not a business analyst who transferred into engineering, and no history of 6-month job hops or dev agency work

Next steps:

Apply via this LinkedIn job post

We will review and reach out if there is a strong match

If aligned, we will introduce you directly to the team

If this role is not the right fit, we may suggest and make introductions to other high-signal startup roles we are actively recruiting for, always with your permission

A quick note on authenticity: This is a real, active role we are supporting in close partnership with the hiring team. We do not post speculative roles and work closely with teams on their actual hiring needs.