Founding Engineer

🚀 Hiring Founding Engineers

We’re a team of Imperial, Stanford and Oxford engineers building a Tier 1 VC-backed AI company focused on scaling financial audit through technology, and are looking for exceptional engineers who have built and shipped before to join us at an early stage and help shape the technical direction of the company.

Our wider team brings together experience from institutions and companies including the U.S. Securities and Exchange Commission (SEC), SoftBank and Grant Thornton, alongside an advisory board of senior audit leaders including former Big Four and IPA-100 partners, PCAOB advisers and leading accounting academics.

Description of the role

You'll architect and build our AI-native audit platform: the investigative brain for a modern

audit firm's engagement teams. We are not building another workflow tool. We are building

the intelligence layer that lets an auditor pull structure and answers out of thousands of messy

client documents and get an analyst-grade result with the audit trail to defend it to a reviewer

or a PCAOB inspector.

You'll own the full stack: agentic AI pipelines, backend services, data layer, and the auditor-

facing product. You'll also own the engineering foundations: turning a working MVP into a

production-grade system with real observability, test coverage, and incident handling. Our

first proof point is a PBC (Provided-By-Client) request-list agent that extracts financial

attachments out of client emails into clean, structured tables for the engagement team. By

reimagining audit as autonomous intelligence, you'll help build the platform we deploy inside

the firms we acquire and that will become the infrastructure for thousands of mid-market

audit firms that support the world’s companies and economy. You'll work directly with the

founders, own technical decisions, and lay the foundation for a potentially massive and fast-

growing company.

Responsibilities and potential impact

● Design and implement RAG and agentic systems that understand corporate registries,

sanctions data, beneficial ownership filings, and adverse media at scale

● Build full-stack services for document processing (PDF/OCR/CSV), async job queues, case

lifecycle orchestration, and risk scoring with confidence-driven UX and human-in-the-loop

controls

● Harden the platform for enterprise: auth controls, role-based access, audit trails, backups, and

monitoring with measurable SLOs

● Establish CI/CD, deployment pipelines, runbooks, and incident response practices from the

ground up

● Propose and engage in cutting-edge AI research related to our mission, particularly around

agentic reasoning over regulatory and financial data

Must haves

● Strong TypeScript and/or Python skills across modern frontend and backend stacks

● Hands-on experience shipping LLM integrations or RAG systems into production user-facing

products

● Experience with document processing, entity extraction, and structured data extraction from

messy real-world sources

● Solid grasp of API design, relational databases, and async job processing

● Proven track record taking a product from "works locally" to reliable production at growing

scale

● Debugging instincts across frontend, backend, infra, and data boundaries - and an ownership

mindset to match

Nice to haves

• 1+ years of experience on technical projects with startup experience strongly preferred

• Knowledge of audit, accounting, or assurance workflows; familiarity with financial

statements, GAAP, or PCAOB standards

• Experience with LangChain, LlamaIndex, or similar AI orchestration frameworks

• Familiarity with accounting systems, ERPs, or financial data providers

• Familiarity with OCR and document intelligence pipelines

• Background in fintech, accounting, audit, RegTech, or other regulated, document-

heavy industries

• Cloud deployment experience and DevOps knowledge in security-sensitive

environments

• Strong product intuition and user experience focus