Finance Engineer Location: Boston Team: Finance Employment Type: Full-Time About VulnCheck Exploitation prevention is only as strong as the intelligence driving those efforts, and most of the industry is still running on intelligence that lacks exploit context. VulnCheck, The Exploit Intelligence Company, delivers structured exploit intelligence on what is actively weaponized in the wild, purpose-built for the data lakes, ETL pipelines, automation, and AI and LLM workflows your infrastructure already runs on, raising the capability of everything it powers.

About The Role

There's a new archetype taking shape in finance: someone who pairs real finance judgment with the ability to build their own solutions — wiring AI agents into the GL, standing up data pipelines without filing an engineering ticket, automating workflows end to end instead of running them by hand. VulnCheck's finance function is scaling across three entities (US, UK, Singapore), and we need someone who builds the systems and AI-driven workflows that keep Finance accurate and fast as we outgrow manual process. That means being genuinely fluent with LLMs (we use Claude) as a working tool, comfortable enough with SQL and APIs to connect our GL, billing, CRM, and spend data without waiting on engineering, and grounded enough in accounting judgment to know when an automated output is right or wrong.

You'll turn raw data into automated models, pipelines, and live dashboards that leadership actually use to make decisions, with the audit trail to back it up.

What You’Ll Do

AI-driven close & reporting workflows. Build Claude-powered workflows that draft variance commentary, flag anomalies, and assemble reporting packages. Financial systems & pipelines.

Connect our GL, billing, CRM, and spend management systems into a single source of truth for ARR, cash, and unit economics, through API/MCPconnections you own rather than tickets you file. Model infrastructure. Own the technical architecture behind the financial model, including version control, forecast wiring, and scenario logic, so it stops needing a manual rebuild every quarter.

Dashboards & reporting automation. Build self-serve dashboards for ARR roll-forward, cohort retention, burn multiple, and deferred revenue that are live and drillable instead of rebuilt by hand each cycle. Close automation.

Take manual steps out of the monthly and quarterly close through scripting, AI agents, and system integration. Audit & controls support. Build documented, repeatable data workflows that hold up under external audit scrutiny (ASC 606, ASC 830, transfer pricing).

Automated doesn't mean uncontrolled. Cross-functional data requests. Be the technical bridge between Finance and GTM, RevOps, and Engineering when a question just needs someone to query the data instead of waiting on someone else to pull it.

What You’ll Bring Technical LLM fluency: real, daily use of Claude (or similar) to analyze data, draft narratives, and check outputs against source documents. You're comfortable building and iterating on prompts, skills, and agents, not just asking one-off questions. Workflow automation: you've actually found a manual, recurring process and killed it, not just wanted to.

Systems integration: you understand how data flows through a GL/ERP, know basic SQL and API principles, and can connect two systems yourself without opening an engineering ticket. Data literacy: you can read a GL, understand revenue recognition and ARR/cohort concepts, and can tell when a dataset is incomplete or wrong before it reaches the board. Behavioral Builds first, asks for headcount second.

Your default instinct is to prototype a fix, not write a request for one. Comfortable owning ambiguity on a small, fast-moving team with few pre-built processes. Can explain automated or AI-assisted output the way you'd defend a journal entry: exactly how a number was produced and why it's right.

Required Qualifications

: Demonstrated hands-on use of AI tools (Claude, Ch