
Neo.Tax is building the easiest and most accurate tax filing and automation software. Our first product simplifies the complex process of applying for the R&D tax credit, putting up to $250,000 back…

Neo.Tax is building the easiest and most accurate tax filing and automation software. Our first product simplifies the complex process of applying for the R&D tax credit, putting up to $250,000 back…
What they do: AI-driven software that automates identification, documentation, and filing for R&D tax credits
Founded: 2019
Headcount (approx.): 29
Recent funding: $10M Series A (Feb 2022)
Tax compliance automation for R&D tax credits and related software capitalization workflows.
2019
Financial software / Tax technology
$3M
Seed announced June 30, 2020
$10M
Series A included participation from GV (Google Ventures), Acrew Capital, Fin Venture Capital and existing seed backers
“Led by Infinity Ventures with participation from GV, Acrew Capital, Fin Venture Capital and existing seed investors”
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Enterprises waste millions on accounting firms to calculate R&D tax credits and capitalize software costs. Neo.Tax is automating this entirely. Our software ingests data from project management, identity management, payroll systems, and leverages AI to complete in hours what used to take weeks or months of manual work for U.S. businesses.
Neo.Tax is seeking a Senior Full-Stack Software Engineer who wants to build products that automate manual enterprise accounting and finance processes. The ideal candidate has expertise in developing complex web applications on both the frontend and backend.
Starting out, you will work on our software capitalization product. Software capitalization is the accounting process of tracking development costs as assets rather than expenses. It's required for compliance and affects how companies report financials. Our customers rely on us to automatically sync accounting data so that they can capitalize development costs monthly and maintain compliance with accounting standards.
We are a remote company, but we prefer to hire in time zones that can overlap with our HQ in Mountain View, CA!
Stock Option Plan (Equity)
Health Care Plans (Medical, Dental, Vision, Short-term Disability)
90% coverage for individual + family
Health & Wellness subsidy
Still interested? Read on for more information!
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Cross-functional collaboration — Work with engineering, data science, and product to evaluate requirements, scope projects, estimate effort, and prioritize work that delivers real value.
Design, develop and maintain web applications — Deliver value for our customers, both externally and internally facing.
Data ingestion at scale — Build pipelines that process millions of records from diverse sources (Jira, Github, payroll systems, accounting software, etc.) reliably and efficiently
Data modeling for flexibility — Design schemas flexible enough to handle different company types, industries, and business processes
Integrations — Read API documentation, build integrations with third-party systems, and handle the inevitable quirks of external data sources.
Customer-facing features — Ship functionality that helps finance teams run their monthly capitalization workflows
Internal tooling — Build tools that help the team operate and debug the system
Automated testing and deployment — Develop and maintain processes to ensure robust systems.
Code Review — Review other engineers’ code and provide timely and valuable feedback to ensure high quality.
Troubleshoot critical issues — Identify root-cause and eliminate recurrence through durable engineering fixes.
Bachelor's or Master’s in CS, CE, or related field.
7+ years professional experience in full-stack development.
Strong proficiency in TypeScript.
Strong proficiency in databases: ORMs, SQL and relational databases.
Strong proficiency in NodeJS and associated frameworks
Proficiency with React or similar frameworks with one-way data binding paradigms.
Proficiency with distributed systems (e.g. asynchronous data processing pipelines).
Ability to effectively design and implement solutions without the help of AI (more info on how we use AI at Neo.Tax below).
Strong problem-solving, analytical, communication, and teamwork skills.
Bonus:
Experience with GraphQL.
Experience with GCP, AWS, or Azure.
Experience with DevOps practices and tools (e.g., Terraform).
Experience with automated testing (unit, integration, end-to-end, black box, mocking, etc.)
Experience working at early-stage, venture-backed startups.
Retirement Plan (401k)
Paid Time Off (Vacation, Sick & Public Holidays)
Family Leave (Maternity, Paternity)
Work From Home (100% remote team)
Series B preparation underway — You'd be joining at a pivotal stage where early employees have meaningful impact on the company's trajectory.
Real traction — Multiple profitable months and 2x revenue growth year-over-year. This isn't a speculative bet.
Big Customers — Mercury, Whoop,
High product-market fit signal
Satisfaction: Customers who love the product because it solves a real need.
Demand: Healthy pipeline of enterprises who are forward thinking about AI and want our product. Series B money will help grow this.
Efficiency: Transitioning engineering focus on scaling our solution and sales process to meet the demands of bigger enterprises now that we’ve seen success.
Small team, big ownership — The engineering team is seven people across three squads. Your work ships to customers and directly impacts the bottom-line.
Greenfield problems — We're still figuring out how to model diverse customer data, scale our pipelines, and automate an industry that's barely been touched by software.
Industry-wide impact — Revolutionizing an outdated process with AI that actually works
The engineering team consists of seven full-time team members (including you) split up across three squads. They work closely with a three-person data science team, one product manager and one engineering manager.
We're early adopters of AI tooling. Engineers use Claude Code daily, and we actively experiment with new AI workflows. We're looking for someone who sees AI as a force multiplier for skilled engineers, not a replacement for knowing how to code.
Typical day
9:00am — You start work. Check your email and Slack. Review notes from yesterday where you left off.
9:15am — You post an asynchronous update in Slack discussing the Linear tickets you worked on yesterday and what you plan to focus on today. You highlight progress and blockers. You raise a risk related to the estimated timeline of your current project. You at-mention someone on the Data Science team to notify them of a change you’re planning to make to an API contract and ask if they’d like to discuss further.
9:45am — Join weekly Engineering Tea Time to discuss technical topics relevant to the whole team.
10:45am — Review two pull requests from your teammates.
12:00pm — Lunch break.
1:00PM — Meet with your Engineering Manager for your bi-weekly 1:1. Ask some questions about the quarterly goals and new enterprise customers we’re onboarding. Provide your manager with feedback on a new code review process we just implemented.
1:30pm — Work on your assigned project. Start a Slack huddle after 30 minutes of investigation to discuss some unfamiliar code with another engineer.
5:00pm — Take some notes on where you should pick up tomorrow. End the day.
If you’re starting a new project soon, you’d participate in a kick-off meeting with all the appropriate stakeholders to ensure you understand the requirements and that the project spec has all the necessary information before you start implementing so that you can deliver what’s expected.
If you’re on-call for that week, you might triage customer issues related to your squad and chat with customer success and product about short-term fixes that will unblock customers and long-term solutions that will improve the product.