Senior Full Stack Software Engineering

Enterprises waste millions on accounting firms to calculate R&D tax credits and capitalize software costs. Tax is automating this entirely. Our software ingests data from project management, identity management, payroll systems and uses AI to do in hours what used to take weeks of manual work.

Tax is seeking a Senior Full‑Stack Software Engineer who wants to build products that automate manual enterprise accounting and finance processes. Our platform team maintains all of our common libraries, data models, third‑party providers, and data ingestion for our asynchronous data processing pipeline. We are a remote company, but we prefer to hire in time zones that can overlap with our HQ in Mountain View, CA!

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 reliably and efficiently.

Data modeling—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 with distributed systems (e.g. asynchronous data processing pipelines).

Proficiency with React or similar frameworks with one‑way data binding paradigms.

Ability to effectively design and implement solutions without the help of AI.

Bonus

Experience with GCP, AWS, or Azure.

Experience with DevOps practices and tools (e.g. Experience with automated testing (unit, integration, end‑to‑end, black box, mocking, etc.).

Experience working at early‑stage, venture‑backed startups.

Stock Option Plan (Equity).

Health Care Plans (Medical, Dental, Vision, Short‑term Disability).

Retirement Plan (401 k).

Paid Time Off (Vacation, Sick & Public Holidays).

Work From Home (100% remote team).

Big Customers — Notion, Mercury, Brex, Whoop, and Thomson Reuters to name a few.

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.

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.

Proactive communicator — You identify and raise risks before they become issues, summarize what you’ve heard, and ask clarifying questions rather than making assumptions.

Business‑aware — You can take product requirements and break them into iterative deliverables that ship value in days or weeks, not months.

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.

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.

1:00 pm — 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. 1:30 pm — Work on your assigned project. 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.

This doesn’t mean you understand all the business logic and code, but you understand the libraries we use and the code structure. You understand the business domain you work in (software capitalization), characteristics of the product’s customers, how they work at a high‑level, and why our software is valuable to them.

You’ve shipped a number of smaller features or bug fixes, in addition to at least one larger project that you implemented mostly independently.

People who have never led an engineering project from inception to delivery without significant guidance.

People who have not taken desired business outcomes and product requirements and broken them up into iterative software deliverables that deliver value in days or weeks not months.

People who rely on AI as a substitute for fundamental engineering skills.

We don't sponsor H‑1B visas. US citizens and Green Card holders are encouraged to apply.

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