TOP NON-NEGOTIABLE SKILLS
1. 10+ years of software engineering experience with deep, hands-on .NET/C# expertise. Experience with AWS, Azure, or Google Cloud Platform is acceptable.
2. Coming out of SMB/Mid Market Financial Services/ Fintech environment
3. System Design & Architecture Ownership : Experience with DDD, CQRS, event-driven architecture Proven ability to independently architect and design complex, distributed systems using sound engineering principles. Looking for ownership, excited, curious builders. Not ICs that are task takers
4. AI-Native : Actively leverages AI-assisted development tools across coding, testing, debugging, and problem-solving. Curious, adaptable, and excited about finding better ways to build and deliver software.
WHAT WOULD MAKE THIS HIRE STAND OUT
1. Someone out of an SMB/Mid Market, not entperise environments. Those profiles the engineers are siloed order takers
2. Strong design instincts : can they articulate why they made certain architectural decisions?
3. Process ownership: Can describe a technical process, framework, or engineering practice they created from scratch rather than inherited.
Interesting Problems You’ll Get to Solve
- Build and evolve scalable card issuing, transaction processing and settlement systems that power critical customer experiences.
- Design reliable integrations across Stripe, banking partners and Zip’s internal platforms, ensuring transactions move securely and accurately at scale.
- Own complex technical initiatives from design through production, making thoughtful tradeoffs across customer experience, reliability, security and delivery speed.
- Contribute to the architecture of event-driven, distributed backend systems using .NET, C#, Azure, DDD and CQRS.
- Build resilient payment systems that operate effectively within evolving regulatory, compliance and risk requirements.
- Improve the reliability, observability and performance of production systems, identifying issues early and strengthening how Zip responds when they occur.
- Partner with Product, Engineering and Infrastructure to navigate technical tradeoffs, de-risk unknowns and deliver solutions that support customer and business outcomes.
- Raise engineering quality through thoughtful design and code reviews, automated testing, monitoring and strong development practices.
- Leverage AI-assisted development throughout the software lifecycle to accelerate delivery, improve code quality and strengthen testing, debugging and technical problem-solving.
- Explore practical applications of emerging AI capabilities to improve engineering workflows, automate repetitive work and help the team build more effectively.
- Mentor and support engineers through pairing, code reviews, technical guidance and knowledge sharing.
What You’ll Bring to the Team
- Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience. A graduate degree is a plus.
- 10+ years of software engineering experience designing, building, testing, and maintaining complex production systems.
- Deep experience with .NET/C#, Azure Cloud Services, and distributed backend systems.
- Experience designing systems using Domain-Driven Design (DDD), CQRS and event-driven architectures.
- Experience building payment infrastructure, card issuing or transaction processing systems, including platforms such as Stripe Issuing, Marqeta or comparable in-house solutions.
- Demonstrated ability to independently own complex technical initiatives from architecture and design through production delivery.
- Strong understanding of reliability, observability, automated testing, system performance and production incident management.
- Experience navigating the security, compliance, and operational considerations involved in building mission-critical financial systems.
- Proven ability to influence technical decisions and partner effectively across Engineering, Product and other technical and business teams.
- Experience mentoring engineers and strengthening engineering practices through code reviews, pairing and knowledge sharing.
- Proven experience leveraging AI-assisted development tools across coding, testing, debugging and technical problem-solving to improve software quality, developer productivity and delivery speed.
- Ability to evaluate and apply emerging AI capabilities to engineering workflows, using sound judgment to ensure quality, security and maintainability.
