Founding Engineer - Remote)
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Summary
Founding Engineer (Ab-Intel) building AI agents that automate tax preparation for large US accounting firms. Day to day: mostly backend work in Python (TypeScript a plus), building LLM/OCR agent pipelines, making backend architecture decisions, and shipping a major product relaunch.
Founding Engineer – Remote (Ab-Intel)
Salary Range: 180k to $240k
We are looking for a Founding Engineer with 2-7 years of experienceto help build AI agents that automate tax preparation for the largest accounting firms in the US. Abacus is profitable, has passed seven figures in revenue in under a year, and is live in 11 of the top 100 firms. We want a high-bar generalist who makes sharp backend decisions and wants to help scale a product that customers already pay for.
Responsibilities
- Build the core tax-automation platform as a generalist: mostly backend, with some frontend
- Help ship the next major version of the product, a big relaunch planned for early next year
- Make backend architecture decisions on your own, working closely with the CTO and Head of Engineering
- Build our LLM and OCR agent pipelines and turn what firms tell us into product
- Work on new products in tax and in other accounting workflows, such as audit
Key Requirements
- Strong Python skills; TypeScript is a strong plus
- Hands-on experience making backend architecture decisions
- Experience at a venture-backed, fast-growing startup (Seed through Series B) is strongly preferred; long tenures at big tech or slow enterprises are a negative signal
- CS degree strongly preferred (Math or Physics also considered) from a top-50 US school, ideally with a strong GPA
- A builder mindset with high ownership and urgency; side projects and 0-to-1 work are a plus
Work experience
- Experience building 0 to 1 at early-stage, venture-backed startups (Seed to Series B, Y Combinator) or as a founding engineer
- Proficiency in Python and TypeScript
- 2 - 7 years of experience as a software engineer
- Has owned features from design to production
- Experience shipping LLM or agent-based features to production
- Owned backend architecture decisions (classic systems, with LLM features on top)
Nice-to-have
- Experience with document extraction or data pipelines at scale
Education
- CS or related technical degree from a Top 50 US university
