About the role
We are looking for a senior backend engineer who can own problems end to end, from unclear requirements to a shipped and observable solution in production. You should enjoy product-minded engineering, including clarifying outcomes, weighing tradeoffs, and delivering incrementally. You should also have a habit of automating repetitive work such as tooling, tests, CI, and internal workflows so the team can focus on higher-value work.
You are expected to use modern AI-assisted engineering tools effectively in day-to-day work, including coding assistants and chat-based models, to move faster while maintaining high standards for quality, security, and code review.
Python is our primary language for this stack. We care most about strong backend fundamentals. If your recent experience is in another language but you are motivated to work primarily in Python, we still want to hear from you.
Why you'll like this role
- Opportunity to explore and learn the payments landscape, including providers, flows, economics, and how they operate at scale in real systems.
- Direct visibility into how your work impacts revenue, efficiency, and scale. Your changes connect to business outcomes, not just internal systems.
- Collaborative environment with strong engineering and product partners. You will work closely with people who care about solving real customer and merchant problems.
What you'll do
- Design and implement features and platform improvements across our backend, including APIs, data access, background jobs, integrations, and operational aspects of payments and related insights.
- Work with product managers and analysts to understand business goals and translate them into reliable and maintainable technical designs.
- Take ownership from discovery through rollout, including implementation, monitoring, incident follow-up, and iteration, especially when the problem is initially ambiguous.
- Improve performance and reliability using approaches suited to our stack, such as SQL and schema design, query tuning, application and worker profiling, queue behavior and backpressure, API latency, and cloud resource usage.
- Reduce toil by identifying manual or error-prone processes for engineering, operations, or internal users, and replacing them with automation, better tooling with safety and observability in mind.
- Operate confidently in production by debugging issues across services, databases, queues, and third-party systems. Participate in code reviews and help raise quality standards.
What we're looking for
Must have
- Approximately 5 to 8 years of professional experience building and operating backend systems, or equivalent depth. We care about impact, not just tenure.
- Strong command of Python for backend services, or experience in a comparable language with the ability to ramp up quickly in Python.
- Solid SQL skills and experience with relational data modeling, along with comfort contributing to analytics and insights that involve non-relational data stores. This includes collaborating with others to interpret and productionize analyses.
- Experience building and consuming REST APIs and integrating external services, including handling webhooks, retries, idempotency, and errors.
- Experience deploying and operating software on a major cloud provider, preferably AWS.
- Proven ability to debug production issues across application, database, and infrastructure layers.
- Experience with multi-tenant SaaS systems and the associated operational and data isolation challenges.
- Comfort using AI-assisted engineering tools such as GitHub Copilot, ChatGPT, or Claude for implementation, review preparation, documentation, and automation, while maintaining team standards for safety and quality.
- Strong communication skills, including asking the right questions, setting expectations, contributing to code reviews, and mentoring junior engineers.
Nice to have
- Experience in payments or fintech, including payment service providers, money movement, reconciliation, webhooks, chargebacks or disputes, and building systems that prioritize correctness and reliability under real-world edge cases.
- Experience with data-oriented projects, including analytics, reporting, or data-heavy product features across multiple data stores; building or maintaining pipelines, exports, or batch workflows; and working closely with analysts or data stakeholders. This is not a data science role.
