Work Location and Eligibility

• This role is remote within Canada, or in-person in San Francisco.
• Visa sponsorship is available only for candidates who are Canadian citizens relocating to the U.S. for the San Francisco office under a TN visa.
• For remote positions based in Canada, candidates must already be Canadian citizens or permanent residents, as we are unable to provide visa sponsorship for remote roles. PR holders must also hold a valid US visa.

About the Role

The company has developed an internal operations platform that supports reviews, case management, and risk-related decisions. While the platform is effective, many workflows still depend heavily on manual review. As transaction and case volumes continue to increase, the company is looking for a Back Office Engineer to build the automation capabilities that will allow the platform to scale efficiently.

This position focuses on designing and implementing intelligent automation across operational workflows. You'll develop systems that reduce manual effort, automate repetitive decision-making, and strengthen fraud prevention through proactive detection rather than reactive investigation.

This is an applied AI engineering role where the solutions you build will directly support high-volume production operations. Success requires building reliable, observable, and well-governed systems that can be trusted in critical business processes.

Working closely with the founder and a small engineering team, you'll have significant ownership over technical decisions and the opportunity to see the impact of your work quickly.

Responsibilities

• Design and implement automation for high-volume operational review processes while ensuring appropriate human review for complex or ambiguous cases.
• Build scalable workflow systems capable of managing increasing case volumes through intelligent routing, prioritization, retry mechanisms, SLA management, and comprehensive audit logging.
• Develop fraud prevention capabilities that leverage real-time signals, monitoring, and decision-making to identify and stop suspicious activity before manual intervention is required.
• Apply AI and large language models where they provide meaningful value, while implementing evaluation frameworks, guardrails, confidence thresholds, and fallback mechanisms to ensure safe, reliable outcomes.

Qualifications

Required

• 3+ years of professional software engineering experience.
• Strong experience building automation platforms or workflow systems, including concepts such as queues, state management, retries, idempotent processing, and auditability.
• Experience delivering production AI or LLM-powered features, with an understanding of model evaluation, safety controls, and appropriate use cases for AI.
• Ability to collaborate with operational teams, identify workflow inefficiencies, and translate business challenges into scalable software solutions.
• Experience developing software within payments, fintech, or another regulated financial environment.
• Familiarity with financial operations such as fraud prevention, chargebacks, disputes, KYC/AML, or related compliance processes.

Preferred

• Experience building fraud detection or risk decisioning platforms.
• Previous collaboration with Operations, Trust & Safety, Risk, or Compliance teams.
• Experience creating evaluation pipelines or testing frameworks for AI-powered decision systems in regulated environments.

Interview Process

• 15-minute introductory conversation with the founder.
• 45-minute technical interview.
• 60-minute technical interview.

Successful candidates will complete two weeks of mandatory onboarding in San Francisco.

Application

Applicants should provide links to both their GitHub profile and personal website as part of their application.

Compensation

• $110K - $175K CAD base salary
• Equity: 0.05% – 0.10%