Founding Backend Software Engineer – Python, TypeScript & AI Agents (0-to-1 Experience)

Location: Remote, United States
Employment Type: Full-Time
Compensation: $180,000 - $250,000 + Competitive Equity
Experience: 2-7 Years (Ideally 2–6 Years)
Work Authorization: US Citizens and Green Card Holders (No Visa Sponsorship)
About the Opportunity:
We are hiring Founding Software Engineers for our client, a fast-growing, profitable AI technology company based in the United States, building AI agents to automate tax preparation for the country's largest accounting firms.
We are looking for high-ownership engineers who have built products from 0 to 1 at early-stage, venture-backed startups, have deep backend engineering expertise, and have shipped LLM-powered or AI agent-based products into production.
This is a primarily backend-focused generalist engineering role with some frontend responsibilities. You'll work closely with the CTO and Head of Engineering, make independent technical decisions, and help scale an established product with paying customers.
Must-Have Requirements - Dealbreakers:
1. Early-Stage Startup Experience (Critical)
Experience building products from 0 to 1 at early-stage, venture-backed startups (Seed to Series B), including Y Combinator-backed companies, or experience as a Founding Engineer.
Demonstrated experience working in fast-moving startup environments with significant engineering ownership.
2. Strong Backend Engineering – Python & TypeScript (Critical)
Proficiency in Python and TypeScript.
Hands-on experience designing, developing, and maintaining backend systems.
Ability to independently make backend architecture decisions.
3. Production LLM / AI Agent Experience (Critical)
Experience shipping LLM-powered applications or AI agent-based features into production.
Experience building backend systems with LLM functionality integrated on top of traditional software architecture.
4. End-to-End Engineering Ownership (Critical)
Demonstrated ownership of software features from initial design through production deployment.
Ability to take independent ownership of technical decisions and product delivery.
5. Education (Baseline Requirement)
Computer Science or related technical degree from a Top 50 US university.
Mathematics or Physics degrees are also considered, ideally with a strong GPA.
Experience & Technical Qualifications:
2–7 years of professional software engineering experience, with 2–6 years preferred for this founding engineering position.
Strong Python engineering skills; TypeScript is a strong plus.
Hands-on experience making backend architecture decisions.
Experience developing and deploying production-level LLM or AI agent features.
Strong understanding of traditional backend systems and integrating LLM capabilities into existing architectures.
Experience at a fast-growing, venture-backed startup (Seed to Series B) is strongly preferred.
A builder mindset with high ownership, urgency, and independent execution.
Side projects and 0-to-1 product development experience are a plus.
Key Responsibilities:
Build the core AI-powered tax automation platform, primarily focusing on backend engineering with some frontend development.
Help deliver the next major version of the product, with a significant relaunch planned for early next year.
Independently own backend architecture decisions while collaborating with the CTO and Head of Engineering.
Develop and scale LLM and OCR agent pipelines.
Translate accounting firms' feedback and requirements into production-ready product functionality.
Build new AI-powered products for tax preparation and additional accounting workflows, including auditing.
Nice-to-Have Qualifications:
Experience with document extraction or large-scale data pipelines.
Side projects demonstrating strong independent engineering ownership.
Experience taking products from concept to launch in 0-to-1 environments.
Candidate Profiles That Are Not a Strong Fit
ML research-heavy candidates without substantial backend systems engineering experience.
Candidates whose experience primarily consists of long tenures at large technology companies.
Candidates primarily experienced in slow-moving enterprise environments rather than early-stage startups.

Work arrangement
Yes