Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
Communication @ 3
Compliance
Machine Learning
Payments
Security @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
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. 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.
About the Team
Stripe will succeed at its mission of increasing the GDP of the internet only if it proves itself worthy of its users’ trust. The Data Privacy Technologies team contributes to this by building systems that allow Stripe to deeply reason about and protect user data at scale. As an engineering team, it leverages system design and applied AI/ML to innovate in data classification and pseudonymization techniques such as tokenization, redaction, filtering, and masking.
Responsibilities
- Design, build, and operate core infrastructure used by all of Stripe’s engineering teams, including systems that automatically annotate and obfuscate sensitive data.
- Make impactful decisions at the intersection of privacy, security, and productivity, including evaluating edge cases, failure modes, and tradeoffs.
- Collaborate closely with legal, product, compliance, operations, and other engineering teams to embed data protection best practices into products and infrastructure.
- Improve engineering standards and processes.
Requirements
Minimum Requirements
- 2–5 years of software engineering experience.
- Experience building and owning highly available, scalable, and performant systems in a high-stakes production environment.
- Empathy, excellent communication skills, and a deep respect for collaboration.
- A learning mindset.
- Ability to think creatively and holistically about reducing risk in a complex, fast-changing environment.
- Ability to drive next steps when encountering ambiguous problems without clear ownership.
Preferred Qualifications
- Data platform or systems experience.
- Applied AI/ML experience.
- Privacy or security experience.