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
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