Staff Software Engineer, Risk Engineering

at Stripe
📍 Toronto, Canada
CAD 208,000-312,000 per year
SENIOR
✅ On-site

Tech Stack

AI AML API @ 4 Communication @ 9 Compliance Debugging @ 6 Distributed Systems @ 8 Java @ 4 LLM Leadership @ 8 Machine Learning NLP @ 3 Observability Payments Ruby @ 4 System Architecture @ 6 Technical Leadership @ 8

Details

Who We Are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Stripe’s mission is to increase the GDP of the internet.

About the Team

Risk Engineering builds systems that protect Stripe from fraud, credit losses, and regulatory risk across user onboarding, compliance, financial crimes, and identity verification.

Financial Crimes Engineering builds systems and controls that enable Stripe to safely onboard businesses in emerging and regulated industries while maintaining compliance with sanctions law, anti-money-laundering rules, and financial partner requirements. The team keeps known bad actors off Stripe, detects emerging threats, and builds AI-augmented tooling to help expert reviewers resolve cases quickly and accurately.

The team operates at scale by screening every user, enforcing jurisdictional restrictions across money movement in real time, and automating signal acquisition and synthesis into investigation workflows. It is re-architecting the screening platform to support new Stripe products with appropriate financial crimes controls, express richer policy as code, and provide a multi-tenant Risk Platform across Stripe’s products and subsidiaries.

Responsibilities

  • Define the technical strategy and multi-year architecture for Stripe’s real-time entity-matching infrastructure, policy enforcement engines, and reviewer tooling.
  • Design and optimize distributed screening engines and detection pipelines that handle entity- and transaction-level requests at scale with strict SLA and uptime guarantees.
  • Build investigations infrastructure that surfaces suspicious activity, collects additional information from users, routes cases to reviewers, and augments human judgment with AI.
  • Serve as the primary technical voice with Legal, Compliance, ML, and Product leaders, translating evolving global regulatory requirements into technical solutions.
  • Lead the architectural evolution toward a multi-tenant screening platform supporting internal product launches and external developer-facing APIs.
  • Set standards for system design, API consistency, and operational rigor across backend and ML-adjacent systems.
  • Mentor senior engineers and lead high-stakes design reviews.
  • Own system reliability, observability, and latency, ensuring production systems adapt to changes in global sanctions lists and traffic spikes.
  • Participate in an on-call rotation for these systems.

Requirements

Minimum Requirements

  • 10+ years of software engineering experience, including 5+ years in a strategic technical leadership role involving core infrastructure, distributed systems, or platform engineering.
  • Proven experience designing, building, and operating high-throughput, low-latency APIs and distributed backend systems at scale.
  • A track record of defining technical roadmaps and driving alignment across multiple engineering teams and cross-functional domains.
  • Hands-on technical depth, including the ability to work from high-level system architecture through code-level performance tuning and production debugging.
  • Exceptional written and verbal communication skills, including the ability to articulate technical decisions to non-technical stakeholders.

Preferred Qualifications

  • Experience in financial crimes, sanctions screening, anti-money laundering, entity resolution, or high-stakes trust and safety platforms.
  • Familiarity with applying LLMs or ML to operational workflows, such as case triage, entity resolution, and review automation; or experience with fuzzy string matching and NLP for entity matching.
  • Experience building investigator or analyst tooling, case management systems, or human-in-the-loop review workflows.
  • Experience building platform products or APIs consumed by internal engineering teams and external developers, including API backward compatibility and client libraries.
  • Experience leading 0-to-1 platform builds or major architectural modernizations from concept to production.
  • Technology experience across multi-language environments, primarily Ruby and Java, as well as modern data infrastructure.
  • Comfort navigating ambiguity and making high-judgment engineering decisions in a fast-moving regulatory environment.

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