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 @ 4
API @ 7
CI/CD
Data Analysis
Data Structures @ 7
Distributed Systems @ 7
Go @ 4
Java @ 4
LLM @ 4
Payments @ 4
Python @ 4
SQL @ 7
Security @ 4
- 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
Stripe is building a dedicated Professional Services practice for leading AI companies, including AI labs, infrastructure providers, and application companies. As an Integration Engineer, you will work directly with engineering teams to deliver complex implementations, migrations, product launches, and international expansions into production. You will also create reusable code, tools, and delivery methods for the wider AI segment.
Responsibilities
- Plan and execute integration engineering end to end, from architecture through code implementation, testing, launch, and stabilization.
- Lead discovery with users, understand their goals and systems, and translate complex use cases into reliable Stripe integration designs.
- Design and build integrations, connectors, migration tooling, automations, and other technical components needed to reach production.
- Act as an ongoing technical partner to users' engineering teams, explaining Stripe's products and API architecture while managing dependencies and trade-offs.
- Investigate and resolve difficult integration issues by inspecting code, reproducing behavior, testing functionality, and coordinating across Stripe teams.
- Lead hands-on-keyboard work, including proof-of-concept implementations, code reviews, testing strategies, CI/CD guidance, and architecture recommendations.
- Review existing integrations and recommend improvements to reliability, performance, maintainability, and readiness for growth.
- Use AI-assisted engineering and delivery tools to reduce manual work and improve implementation speed and quality.
- Partner with Product and Engineering to identify recurring user needs and opportunities to improve Stripe's products, APIs, and tools.
- Create reusable technical assets, including code, reference architectures, migration methods, guides, dashboards, and data analysis.
Requirements
- 6+ years of experience in software engineering, integration engineering, solutions engineering, technical consulting, or a comparable customer-facing engineering role.
- Ability to write code in Go, Java, Python, C#, C++, or similar languages, and quickly understand and debug unfamiliar code.
- Strong generalist technical experience, including SQL and an understanding of APIs, data structures, distributed systems, and software architecture.
- Experience designing or delivering integrations between complex systems and third-party APIs.
- Understanding of API security, reliability, testing, and production-readiness practices.
- Ability to move between architecture and implementation, using code, logs, and data to solve open-ended problems.
- Ability to explain technical concepts clearly to engineers, business stakeholders, and senior leaders.
- A user-first approach and confidence leading technical work across multiple teams in an ambiguous, fast-moving environment.
Preferred Qualifications
- Experience with AI-native companies, developer infrastructure, cloud platforms, or other rapidly scaling technology companies.
- Experience with payments or financial infrastructure.
- Experience using AI coding assistants or LLM-based agents in engineering work.
- Experience delivering migrations, multi-product implementations, or international launches.
- Strong technical writing skills and a willingness to teach and mentor others.
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