Orion Digital Corp. operates real revenue-generating platforms across lending, investing, and payments.
- We are regulated.
- We have production infrastructure.
- We have legacy systems.
- And we are redesigning the core.
We are in the middle of becoming AI-native, not as a feature layer but as a structural shift in how software is built, how decisions are made, and how workflows operate.
This is not greenfield experimentation.
This is live-system transformation.
If you want to help rebuild a functioning fintech company into an AI-native operating model, this role is aligned.
The Context
AI is compressing the cost of software creation and decision-making toward zero. The advantage is no longer who ships more code. It’s who redesigns systems around intelligence.
Orion is restructuring around that reality.
We are:
- Replacing manual workflows with agents
- Embedding intelligence into core systems
- Redesigning deterministic architectures to incorporate probabilistic reasoning
- Building evaluation and reliability frameworks where none previously existed
This transformation is active and underway. You will help drive it.
The Role
You will design and ship production-grade AI systems inside a live fintech environment.
This is not prompt engineering.
This is systems engineering during architectural transition.
- Redesign legacy workflows into AI-native systems
- Architect LLM-backed services integrated with production APIs
- Build multi-step agents that reason and take actions across internal systems
- Design hybrid architectures combining deterministic logic with probabilistic reasoning
- Implement model routing and cost-aware execution
- Build fallback and confidence-aware systems
- Own reliability, evaluation, and observability
- Ship safely in regulated, production environments
You are not joining a finished AI-native machine.
You are helping build it.
What You’ll Work On
Transforming Existing Systems- Replace manual review processes with AI agents
- Introduce structured-output-first services into legacy APIs
- Embed intelligence into lending, investing, and operations systems
- Migrate deterministic decision flows into adaptive models
- Tool-calling agent architectures
- RAG systems connected to internal data
- Orchestration pipelines across services
- Evaluation frameworks for probabilistic systems
- Monitoring for latency, cost, hallucination risk, and drift
- Compliance-aligned guardrails
- Introduce AI-native development workflows
- Build internal leverage tools
- Reduce human dependency in repeatable processes
- Improve output without increasing headcount
What You Bring
Core Engineering- 4+ years building production backend or full stack systems
- Strong Node.js and TypeScript experience
- Experience with APIs and distributed systems
- Experience building and shipping mobile applications (React Native or similar)
- Comfortable operating in complex, real-world systems
You have shipped AI systems beyond prototypes.
You understand:
- Structured outputs and tool calling
- Agent orchestration patterns
- RAG architectures
- Prompt versioning and evaluation
- Latency and cost trade-offs
- Debugging LLM behavior in production
- Cloud-native experience (AWS preferred)
- CI/CD and infrastructure-as-code
- Event-driven architectures
- Comfort working in regulated or data-sensitive environments
Bonus:
- Python for experimentation
- Experience migrating legacy systems
- Experience building internal AI platforms
How You Operate
- You take ownership of outcomes.
- You are comfortable replacing existing systems.
- You move quickly without lowering standards.
- You think in leverage, not effort.
- You measure impact.
- You hold your own work to a high bar.
You are not intimidated by ambiguity or transition.
Performance Expectations
You will be measured on:
- Successful migration of workflows to AI-native systems
- Production reliability and durability
- Measurable reductions in manual effort
- Intelligence lift across product and operations
- Engineering leverage created
- Standards raised across the team
This is a transformation role.
What This Role Is Not
- Not a prompt experimentation role
- Not AI theatre
- Not a low-ownership environment
This is real system redesign inside a live fintech company.
Why This Is Rare
Most companies experimenting with AI are startups without legacy constraints.
Very few engineers get to:
- Re-architect real revenue-generating systems
- Transform a public fintech company
- Replace human workflows with intelligent systems at scale
- Define what “AI-native” means inside a regulated environment
This is that opportunity.
Compensation
Base salary: $115,000 to $150,000 CAD
Compensation aligned with demonstrated AI capability, ownership, and impact.
Next Steps
If you are energized by transformation rather than intimidated by it, we encourage you to apply.
We hire deliberately. Every addition to the team should raise the average.
