Staff Full Stack Engineer, Identity

Role Description

As a Full Stack Staff Engineer on the Identity team, you will own the technical direction of one of Stripe's most strategically important product areas. This is not a role defined by task execution — it's a role defined by technical judgment, architectural influence, and the ability to turn an ambitious vision into a reliable, scalable system.

Responsibilities

• Own technical strategy — Define the architecture for Identity's core systems (Identity Store, headless verification platform, fraud detection infrastructure), make build vs. buy vs. partner decisions, and surface technical risks before they become customer-facing failures.
• Lead 0-1 platform development — Architect net-new systems including the Identity Store, Networked Identity platform, and advanced fraud detection pipeline (behavioral biometrics, deepfake discriminators, adversarial training). Drive the evolution from a hosted-UI product to a headless-API and embedded-components platform.
• Drive cross-functional alignment — Be the primary technical voice in roadmap and resourcing discussions. Partner with ML, product, legal, and engineering leads across Risk, Fraud, Link, Connect, and Crypto to ensure Identity's abstractions serve the full breadth of Stripe's product surface.
• Raise the technical bar — Set engineering standards across ML, backend, mobile, and front-end; lead design reviews; and mentor senior engineers on the judgment needed to operate a high-stakes, externally-facing product.
• Operate with ownership — Be accountable for reliability, scalability, and security of the systems you design — including the observability and alerting that catch model drift and fraud pattern shifts before customers do.

Qualifications

• 10+ years of software engineering experience, including 5+ years of experience in a strategic technical leadership role.
• Experience leading engineering team(s) working on API design, abstractions, frameworks, or client libraries (e.g. building internal or external developer products).
• Proven track record of delivering pragmatic solutions that accelerate business growth.
• Ability to adjust conversations from high-level discussions to detailed coding.
• Clear and persuasive writing and in-person communication.

Requirements

• Experience with identity verification, fraud detection, or trust and safety systems — especially systems with adversarial inputs at scale.
• Familiarity with ML systems in production: model serving, training pipelines, observability, drift detection, and the feedback loops that keep models accurate under adversarial conditions.
• Experience building platform products with multiple consumer types — internal platform teams and external developers — where API backward compatibility and abstraction quality are first-class concerns.
• Prior experience with 0-1 product builds: you've started with a blank page and ended with a production system, and you have clear opinions about what makes that process go well or poorly.
• Experience across a range of software languages and frameworks; our stack includes primarily Ruby and TypeScript on the backend, Python for ML and data pipelines, with infrastructure spanning Kafka, Temporal, Protobuf, React, SQL (Spark and Trino dialects), Airflow, Bazel, Mongo, Splunk, and Prometheus.
• Experience navigating ambiguity in a fast-moving organization — you can make confident technical decisions with incomplete information and update gracefully when new constraints emerge.