About the Role
You are building the machine underneath the machine. The patterns you create will define how financial data moves and settles across the ledger, and how safely and quickly everyone else can build on top of it. The work spans core system design, integrations infrastructure, and the abstractions that make a growing codebase coherent. Financial data holds systems to a standard most software never has to meet - and that standard starts here.
Responsibilities
- Own the foundational patterns that govern how financial data moves, matches, and settles.
- Build the core primitives that product builders extend rather than reinvent: counterparty enrichment, object-arrival matching, transaction reconciliation.
- Build abstractions that let engineers and agents contribute safely, without needing to understand the full complexity beneath.
- Be the architectural authority the team looks to - reviewing approaches, shaping how new work lands, keeping the codebase coherent.
Requirements
- Deep technical foundations and a long track record of building systems that other engineers rely on.
- 7+ years of engineering experience, with a strong foundation in computer science.
- Deep, practical AI integration into your engineering workflow.
- Deep experience designing and building distributed systems, core platform primitives, or foundational infrastructure.
- Strong instincts for abstraction - you know how to create patterns that are both powerful and hard to misuse.
- An understanding of what it means to build on financial data, with non-negotiable requirements for accuracy, auditability, and reliability.
- Experience working in a codebase where other engineers depend on your work.
- Comfortable operating with autonomy and forming strong technical opinions.
- High agency. You identify the problem, form a view, and act.
- AI-forward. You've changed how you work because of AI - not as a novelty, but because of how it lets you build.
- Strong opinions. You have a perspective and you share it.
- Ownership. You feel responsible for outcomes, not just doing your part.
- Curiosity. You go deep without being asked.
- Optimistic. You believe that things can improve, problems can be solved, and people are generally trying their best.
Skills
- AI integration
- Distributed systems design
- Core platform primitives development
- Foundational infrastructure development
- Abstraction
- Accuracy
- Auditability
- Reliability
- Autonomy
- Technical opinions
- Fintech experience
- Accounting software experience
- Financial infrastructure experience
- Ledger systems familiarity
- Reconciliation familiarity
- Payment processing familiarity
- Integration infrastructure at scale experience
- Workflow engines experience
- State machines experience
Location
- Toronto
Work Type
- In-person
- Full-time
Experience Level
- 7+ years of engineering experience
Education Level
- Strong foundation in computer science
Salary/Compensations
- 170,000–230,000 CAD
- plus equity
Benefits
- Competitive pay
- 100% covered health insurance
- Work laptop provided
- Flexible PTO
About the Company
- Alloy River builds agentic applied AI for finance and accounting.
- We believe accounting should be intelligent, structured, and operationally decisive.
- Our mission is to transform finance from a slow, labor-intensive, reporting function into a real-time, strategic engine for profit and control.
- We re-architected the general ledger from first principles, and layered automation, workflow orchestration, and applied AI directly into its core.
- We raised over $30m to date from Portage Ventures, Electric Capital, Elad Gil, and angels like Tobi Lütke, Balaji Srinivasan, and many more.
- We’re scaling what we do with the best builders, operators, and craftspeople in the world.
- Help create a category-defining product with a real impact on business owners.
- Work in-person with people who are excellent at what they do and fun to be around.
- Join early and shape the future of an industry.
Equal Opportunity
- We may use AI to help review candidate applications, but the final decision is always made by a human.
