Sunbit builds financial technology for real life.

Our technology eases the stress of paying for life’s expenses by giving people more options on how and when they pay. Founded in 2016, Sunbit offers a next-generation, no-fee credit card that can be managed through a powerful mobile app, as well as a point-of-sale payment option available at more than 25,000 service locations, including auto dealership service centers, optical practices, dentist offices, veterinary clinics, and specialty healthcare services. Sunbit was included on the 2022 Inc. 5000 list.

The financial technology company has also been named a Most Loved Workplace®, Best Point of Sale Company, and a Top Fintech Startup by CB Insights. We use cutting-edge innovations in financial technology to bring leading data and features that allow individuals to be qualified instantly, making purchases at the point of sale fast, fair, and accessible for consumers from all walks of life. We create value focused on our core values; we work tirelessly to ensure that Sunbit becomes available to everyone, everywhere.

We invite you to #UnleashYourCuriosity and join our ever-growing R&D organization.

What You’ll Do:

Join Sunbit's Card Risk Squad and take a central role in building the systems that power one of the core products of the company – our credit card.

We’re looking for a Senior Software Engineer to join a dynamic and high-impact team that owns the entire risk infrastructure behind our credit card. This includes real-time decisioning systems, integration with advanced ML models, risk engines, and credit strategies that directly impact Sunbit's financial health and customer experience.

You'll collaborate closely with data scientists, backend developers, and product stakeholders to build systems from scratch, design complex architectures, and ensure scalable, high-performance infrastructure capable of making split-second decisions.

This is a unique opportunity to join a fast-growing fintech company, influence the product at its core, and shape the way credit and risk are managed across our platform.

Key Responsibilities

• Design, implement, and maintain large-scale backend systems for real-time risk and credit decisioning.
• Build and optimize data pipelines and streaming systems that support our risk and ML models.
• Work closely with data scientists to integrate predictive models into production.
• Build microservices and internal tools that serve thousands of users and scale with company growth.
• Own projects end-to-end — from requirements and architecture to testing, deployment, and monitoring.
• Collaborate with engineering and cross-functional stakeholders to ensure business alignment and smooth delivery.
• Drive best practices in software engineering — from code quality and security to performance and maintainability.

What You’ll Bring:

• A strong backend engineer with 7+ years of hands-on experience.
• Experienced in designing and maintaining complex distributed systems.
• Passionate about data and infrastructure: queues, stream processing, and data-centric microservices.
• Excited to work on both product-oriented and infrastructure-oriented challenges.
• Flexible, resourceful, and proactive.
• Enjoy working closely with ML teams, learning new domains, and diving into unfamiliar territory when needed.

Requirements:

• 7+ years of backend development experience, preferably in Python (but open to strong engineers in other languages).
• Deep experience with databases (SQL or NoSQL), queues, and streaming platforms.
• Experience working with complex architectures, microservices, and production-scale systems.
• Proven ability to work independently and deliver high-quality solutions in fast-paced environments.
• Strong understanding of software design principles and engineering best practices.
• Fluent in English (working language).

Nice to Have

• Prior experience in a fintech or risk/credit environment.
• Experience with ML model integration in production systems.
• Hands-on experience with AWS, Docker, Kubernetes, and CI/CD pipelines.
• Familiarity with web frameworks (e.g., FastAPI, Flask, Django).
• Experience working closely with data scientists or building ML-based systems.