Stripe
From Stripe's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
What you’ll do You will own a meaningful part of a risk-decisioning problem from investigation and design through implementation, rollout, measurement, and iteration.
Who we are
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. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.
Supportability Decisions is a Dublin-based engineering team within Supportability Engineering, part of Risk Engineering. We own the “how a business sells” side of Supportability: determining whether a user’s declared business, web presence, account configuration, and observed transaction behaviour align with Stripe’s standards.
Our core domain includes transaction-laundering detection and decisioning, web-presence and URL-policy controls, and low-quality e-commerce detection. We consume the signals and evaluations that support decisions in these spaces and convert them into evidence-based and auditable determinations that can be shared with the rest of the Supportability platforms.
The pitch is: join a high-ownership team solving some of Stripe’s hardest risk problems. We build technology that helps Stripe distinguish legitimate businesses from bad actors at scale, combining sophisticated engineering, AI-assisted investigation, and meaningful real-world impact.
You will own a meaningful part of a risk-decisioning problem from investigation and design through implementation, rollout, measurement, and iteration. You will help build both the domain capabilities and the modern agentic infrastructure required to make Supportability decisions consistent, stateful, explainable, and appropriate to the business, product, and moment in time. Depending on team priorities and the candidate’s experience, this may include:
Building the Supportability Decision Layer: a durable service and API through which automated systems, agents, and human reviewers can request, produce, retrieve, and understand canonical decisions.
Developing the infrastructure that enables agentic investigations to synthesize policy, business identity and history, product context, risk appetite, and multiple assessment signals into explainable, confidence-calibrated decisions.
Improving the transaction-laundering agent’s policy grounding, evidence quality, risk tiering, precision and recall, and use of behavioural, dispute, and other relevant signals.
Designing durable decision state and history, including traceability from supporting evidence through reasoning and applied consequence, and validity and refresh policies that prevent stale outcomes from persisting.
Building governed, reusable configuration and integration patterns that adapt decision capabilities across products, partners, countries, and permitted risk appetites without creating bespoke systems for each use case.
Building reliable backend workflows on shared Supportability and Risk Platform infrastructure.
Making complex risk decisions explainable to reviewers and affected users.
Using data and feedback from outcomes, appeals, and corrections to improve decision quality while balancing the identification of bad actors against avoiding unnecessary harm to legitimate businesses.
Modernising URL enforcement, including when and how URL checks run, reducing unnecessary review volume and user friction, and supporting migration away from legacy systems.
Expanding shared SAE/SPO decisioning foundations, including due-diligence support and product-scoped remediation and appeal capabilities.
Improving the Process Orchestration Framework and moving workflow code into more maintainable platform packages.
Contributing to future work in automated LPM URL screening, low-quality e-commerce detection, wider web intelligence, and active test charges.
We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
2 - 7 years of industry software engineering experience (does not include internships or co-ops)
You work effectively across the stack from top to bottom, comfortably navigating codebases with different languages and tools
You're equally comfortable shipping user-facing experiences as you are writing custom queries to analyze experiment results
Strong coding skills in any programming language (we understand new languages can be learned on the job, so our interview process is language-agnostic)
Strong collaboration skills, with the ability to work across workstreams within your team and contribute to your peers' success
Ability to thrive on a high level of autonomy and responsibility, and think of yourself as entrepreneurial
Interest in working as a generalist across varying technologies and stacks to solve problems and delight both internal and external users
Experience working in high-growth teams similar to Stripe
Experience building financial systems or tools for financial experts
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