Job Category: Tech & Development

The opportunity

You get to build a category-defining tax product from a blank page, in the window where one senior engineer with frontier AI tooling can deliver what used to take a team of five.

Tax is a high-stakes, regulated, globally enormous market that has barely been touched by AI-native software. taxOS is built by founders who know tax cold, with a domain reviewer on the bench and a fractional CTO already in place. The substrate, the calculation engine, the AI orchestration, the practitioner workspace: all of it is yours to architect and ship through to a live filing season.

This is the moment to build the thing that would have taken a venture-backed team eighteen months to assemble, in a fraction of the time, with your name on it.

The autonomy

You are not joining to execute someone else’s plan. You make the substrate choices. You set the architecture. You own CI/CD, observability, security posture, and the regression discipline a tax product demands.

You will push back on the founders when the product direction is wrong, and commit fully once a decision is made. They are tax experts, not engineers, and they know it. Your judgment is why we are hiring you.

We have a preferred stack documented in the PRD: TypeScript / NestJS, PostgreSQL with pgvector, React, Anthropic Claude as primary LLM, AWS or Cloudflare for substrate. Nothing is locked in. If you arrive in the first month with a strong reason to change a choice, we want to hear it. Two non-negotiables: it has to be a modern web and cloud stack, and it has to be mainstream enough that we can hire the second and third engineer who already know it.

For the first year the team is deliberately small and trust-based: the two founders, you, and a second engineer, plus a third who joins around month 3/4 to push UI velocity. No hierarchy to navigate. No committee to convince. You build the system.

What you will actually do

• Architect the platform and own the substrate choices.
• Design the ledger. taxOS needs a tax-aware data model that captures entity relationships, source documents, and the time dimension tax demands (transaction date, filing period, amendment history, audit trail). Graph, event-sourced, bitemporal, or some combination: that call is yours to make and defend.
• Build the deterministic calculation engine and the agentic orchestration layer that surrounds it. The orchestrator decomposes practitioner intent into deterministic calculation steps and probabilistic classification steps, with explicit guardrails, retries, and human-in-the-loop checkpoints between them. Single-prompt chains are not the bar.
• Ship document ingestion, classification, and the practitioner workspace through to a live filing season.
• Stand up CI/CD, observability, security posture, and the regression discipline a tax product demands. A 0.5% silent calculation error is a serious failure, and the system has to make that class of error impossible.
• Walk a practitioner through the product in two minutes. Selling it to a senior accountant is part of the job.

What “founding engineer” means here

You write the code. We are not hiring a CTO, an architect-on-paper, or a manager. The product gets built by the person we hire, with judgment, taste, and the 2026 toolchain.

If you drifted into management, architecture, or fractional work because pure coding stopped being interesting, and you have come back to building because AI tooling has changed what one person can deliver, this seat was built for you.

What we care about underneath the stack

• Production experience with frontier LLMs. Shipped systems, evaluation harnesses, a real cost-per-call number you can defend. Not prototypes.
• Agentic orchestration in production. Multi-step agent workflows with tool use, retries, fallbacks, and human-in-the-loop checkpoints. You have a view on when to constrain an agent and when to let it reason.
• Graph or event-based data modelling. Comfortable with graph databases, event-sourced ledgers, or bitemporal data, with a view on when each is the right tool. Tax is fundamentally relational and temporal, and the ledger has to reflect that.
• A track record in a regulated or high-stakes domain. Fintech, healthtech, tax, payments, legal tech. You have internalised that probabilistic outputs need deterministic guardrails and that audit trails matter from day one.
• Strong on either Python or TypeScript, willing to use whichever the project needs.
• Comfortable owning the full stack: backend, data model, frontend, infra. The job is not divisible into roles.

Who you are

A few things matter more than years of experience.

• You are excited about what AI changes for builders, not threatened by it. The right person sees Claude and similar tools as a lever, not a risk.
• You are a strong communicator. You will translate the founders’ vision into a working system, and translate back when something they want will not work. That conversation has to be crisp.
• You overlap Europe or US East Coast working hours comfortably. Async is fine once the product is built. While you are still figuring out what you are building, same-ish hours matter.
• You are senior enough to be opinionated and humble enough to be wrong. Both are the job.
• You do not need a tax background. Domain expertise comes from the founders and the senior practitioner.

Engagement

• Full-time, fully remote within Europe or US East Coast.
• Twelve-month minimum commitment. The expectation on both sides is that this becomes long-term.
• Competitive base salary, benchmarked to senior engineering in your region.
• Founding-engineer equity: 1.5 to 3.0 percent post-seed, four-year vest, one-year cliff.
• Mutual NDA and standard IP-assignment terms before any confidential material is shared.

How to apply

Apply below. Include:

• One or two production systems you have personally built that are comparable in complexity. What it did, what you owned, what you would do differently today.
• Links to code, writing, or anything that shows your work. A real artifact beats a polished CV.
• Your location, notice period, and target base salary.
• One sentence on why taxOS specifically. Not why startups. Why this one.

We reply to every serious application.

Build AI That Makes Accounting Autonomous

We’re creating AI that handles the entire complexity of accounting workflows autonomously – from transaction processing to report preparation, from reconciliation to compliance checks. The accountant remains for final review and filing, but the heavy lifting becomes entirely autonomous.

Our approach: continuous learning from millions of real transactions creates compound intelligence that no static model can match. Every transaction teaches our system. Every correction improves tomorrow’s decisions. Every client pattern becomes permanent knowledge. While others retrain models quarterly, our AI evolves every second from actual usage.

What You’ll Build

• Continuous Learning Architecture: Systems that turn millions of daily transactions into compound intelligence without model retraining.
• Autonomous Workflow Systems: AI that completes complex, multi-step processes independently – categorization, reconciliation, report generation.
• Client Intelligence Layers: Architecture where each business’s AI becomes uniquely accurate through learned patterns.
• Industry-Defining Benchmarks: Evaluation frameworks that establish what autonomous accounting means.

You’ll work directly with leading AI labs – Anthropic, OpenAI, or others – to build custom capabilities that don’t exist in any current API.

Why This Matters

We’re eliminating the drudgery that consumes millions of hours – the manual categorization, the endless reconciliation, the repetitive compliance checks. Accountants should focus on strategy and decisions, not data entry and matching. When this works, accounting becomes a strategic function, not an operational burden.

The Challenge

Building AI that handles real money autonomously requires solving unsolved problems:

• Online learning with financial-grade accuracy guarantees
• Client-specific optimization at million-user scale
• Continuous improvement without catastrophic forgetting
• Explainable decisions for audit trails and compliance

These aren’t research questions – you’ll solve them in production, processing billions in real transactions.

What You Bring

• Track record building AI systems that redefined what’s possible.
• Deep expertise in online learning, continuous adaptation, and memory architectures.
• Experience shipping complex systems at scale with real-world constraints.
• Ability to partner with AI labs to push beyond current capabilities.
• Vision for how AI achieves true autonomy in professional work.

The Opportunity

Define the architecture that makes professional work autonomous. Build systems that transform accounting from manual labor to strategic oversight. Create the intelligence layer that makes continuous learning possible at scale.

You won’t implement our vision – you’ll create it.

Build Autonomous Systems That Actually Work

We’re at 80% automation today, building toward 95% autonomous accounting. Looking for engineers who want to ship AI that eliminates entire categories of human work.

The Mission

Build autonomous agents that complete entire accounting workflows without human intervention. Your code will power self-running reconciliation, intelligent categorization, and eventually full month-end close. This isn’t about incremental improvement – it’s about making manual bookkeeping obsolete.

What You’ll Build

• Self-improving reconciliation agents that match transactions across 170+ currencies, crypto wallets, and payment processors with 98%+ accuracy.
• Multi-agent orchestration systems that coordinate complex workflows – from invoice processing to financial reporting.
• Document intelligence pipelines that extract and process any financial document.
• Reasoning agents that detect anomalies, explain decisions, and self-correct.
• Real-time processing systems handling millions of transactions with sub-second response times.

Non-Negotiable: You Must Code with AI

We only hire engineers who are highly proficient with AI tools. You should be using Claude/GPT-4/Copilot daily to ship 3-5x faster than traditional development. If you don’t actively code with AI, this role isn’t for you.

The Technical Challenge

• Build agents that improve themselves – learning from corrections and patterns.
• Handle infinite edge cases across 21,000+ bank feeds and payment methods.
• Create explainable AI that accountants trust with their clients’ finances.
• Design fault-tolerant systems that self-heal and never lose a transaction.
• Scale from SMEs to enterprise volumes without architecture changes.

Core Technical Work

• Implement advanced RAG systems with domain-specific financial knowledge.
• Build custom model training pipelines using AWS SageMaker.
• Design event-driven architectures for real-time agent coordination.
• Create feedback loops where agents learn from each correction.
• Develop testing frameworks for autonomous systems with real financial implications.

What You Need to Show Us

• You’ve built real AI/ML systems – production, research, or compelling personal projects.
• Strong Python skills and experience with modern AI frameworks.
• Hands-on work with LLMs, agent architectures, or autonomous systems.
• You ship working code, not just experiments.
• You can reason through complex system design problems.

Technical Environment

• AWS AI infrastructure: Bedrock, SageMaker, Claude, Nova models.
• Distributed processing handling millions of daily transactions.
• Real-time event streaming and complex orchestration.
• Multi-region deployment, 24/7 uptime requirements.
• Python-heavy backend with modern ML infrastructure.

What Makes You Successful Here

• You’re obsessed with automation – doing anything manually twice bothers you.
• You think in systems – how agents work together, not just individually.
• You measure success by customer hours saved and errors prevented.
• You’re comfortable with ambiguity and can define your own path.
• You want to prove what AI can actually do beyond demos and prototypes.

The Reality Check

• This is hard – you’re automating work that humans have done for centuries
• You’ll deal with real money, real businesses, and zero tolerance for errors
• The edge cases are endless and sometimes bizarre
• You’ll need to learn accounting concepts (we’ll teach you)
• Your code will process billions in transactions

The Opportunity

Accounting is a $88B market where most “AI” is just better search or rules engines. We’re building agents that actually complete the work. You’ll prove that autonomous systems can handle complex, high-stakes tasks that everyone said required human judgment.

This is your chance to build AI that runs businesses, not chatbots that talk about running businesses.

What We Offer

• Competitive salary based on experience
• Ship to production in your first week
• Own critical systems from day one
• Work with a small team where your contributions immediately matter
• Remote-first with quarterly team meetups
• Learning budget for courses and resources

To Apply

Show us:

• A project where you’ve built agents or complex automation
• Your approach to making systems truly autonomous
• Code that demonstrates your thinking (GitHub, notebooks, anything)
• Why you’re excited about replacing human work with AI

If you want predictable work on marginal improvements, this isn’t for you. If you want to build autonomous systems that handle real-world complexity at scale and define what AI can actually do, let’s talk!