This role pays more than
70%
of similar roles. Most pay
$152,450–$211,468
— the shaded band above.
At the midpoint, this role pays about
$207k
versus about
$182k
for comparable roles.
Based on 240 similar postings.
Employer
About Stripe
Stripe is a financial infrastructure platform for internet businesses, providing payment processing, billing, fraud prevention, and banking-as-a-service APIs to businesses of all sizes globally. Industry: Payments Infrastructure & Financial Technology
Stripe currently has
173 open roles
on FindRole.
Listed pay typically runs
$190,400–$285,600
across 171 roles with salary data.
Enterprise Risk Management (ERM) Program & Automation Lead, MALPB is a hybrid role for a technically fluent risk architect within the Risk and Compliance team. The successful candidate will own the enterprise risk program end-to-end, balancing two primary functions. One third of the role involves executing the ERM framework, including RCSA cycles, managing the control library, and synthesizing risk scorecards for executive reporting. The remaining two-thirds focuses on AI and control automation design, where the individual acts as a hands-on developer to build LLM tools, automated evidence-collection scripts, and real-time monitoring workflows. To succeed, the candidate must possess expertise in Python, SQL, and REST APIs, alongside experience with LLM orchestration and prompt engineering. This role addresses the challenge of building an AI-native risk management system within a complex, fast-moving regulatory environment for financial infrastructure.
Implement the enterprise risk management framework across all business lines and operational functions.
Execute annual and semi-annual Risk and Control Self-Assessment cycles with independent challenges to first-line ratings.
Maintain the Master Control Library, Central Risk Register, and universal Risk Taxonomy.
Monitor Key Risk Indicators against approved thresholds and trigger formal remediation plans when breached.
Synthesize risk metrics into quarterly scorecards for presentation to executive leadership and the Board of Directors.
Develop automated data extraction pipelines using SQL and APIs to sample control verification data.
Build and implement LLM agents to perform semantic analysis on logs and policy documents to flag anomalies.
Engineer GRC infrastructure to automate self-attestation workflows and transition toward real-time monitoring dashboards.
What we're looking for
A Bachelor's degree in Computer Science, Data Science, Finance, Business, or a related quantitative field.
At least 8 years of experience in enterprise risk management, operational risk, or risk advisory within a regulated financial institution, FinTech, or Big 4 tech-risk consultancy.
Proven track record of rolling out and integrating risk programs including RCSAs, KRIs, and Control Libraries into active business units.
Hands-on experience writing Python and SQL to query databases, manipulate data, and interface with web/REST APIs.
Experience using LLM APIs, prompt engineering, or automated workflow engines to analyze unstructured text or automate routine tasks.
Exceptional communication skills to challenge senior leaders and translate complex risk data into concise narratives for Board-level reporting.