Most database engineering job descriptions read like a checklist of maintenance tasks, migrations, and optimization tickets. This one is different. At pmtbox (“Payment Box”), we’re building a fintech platform that manages payments-related risk, fraud, chargebacks, card declines, and related operational workflows for retail clients. We’re a VC-backed fintech with a small team, over 1,000 active clients, and big ambitions, and we’re looking for engineers who want to build systems, not just maintain them. We’re looking for a Database Engineer who wants to help designscale, and tune the data foundation behind a rapidly growing fintech platform.

If you’ve spent your career in environments where database work is isolated to ticket queues and reactive support work … this role might feel very different. We’re looking for engineers who:

• Think deeply about data architecture, scalability, and operational reliability
• Enjoy solving complex systems and data workflow problems
• Build infrastructure and tooling proactively rather than reactively
• Care about performance, integrity, observability, and long-term maintainability
• Use AI as a force multiplier in their engineering workflow
• Think beyond queries and into the operational systems powered by data

You’ll be building real systems alongside founders, including a technical co-founder with deep industry experience and expertise, and a small, high-performing engineering team. Expect to:

• Design and optimize scalable relational database architecture across a growing fintech platform
• Improve database performance, indexing strategies, query optimization, and operational reliability
• Help architect and evolve complex data models tied to payments, fraud, risk, operational workflows, and reporting systems
• Build tooling around data validation, migrations, observability, integrity checks, and operational monitoring
• Improve reporting, analytics, and internal operational data workflows
• Partner closely with backend and frontend engineers to improve system performance and scalability
• Contribute to architectural decisions around data storage, caching, replication, and long-term scalability
• Use and refine AI-assisted development and operational workflows
• Improve database testing, CI/CD processes, and deployment reliability

This is not a role where everything is already defined, but it’s also not greenfield. You’ll be building within established systems and patterns while helping evolve them over time. Our engineering team is intentionally small and high-ownership. We currently support over 1,000 active clients across a Rails/Postgres/Redis stack with AI-assisted development workflows integrated into daily work. We maintain a tests-first culture, CI pipelines, structured project context, and operational guardrails that allow engineers to move quickly without sacrificing quality or reliability. This isn't a “move fast and break things” environment. It’s a “move fast because the guardrails are good” kind of environment. You’ll have real autonomy within well-defined boundaries: clear architectural patterns, collaborative decision-making, tested systems, and documentation that allows you to ship independently without constant oversight.

We care less about years of experience and more about how you think, design systems, and solve operational problems. You might be a great fit if you:

• Have strong experience working with relational databases such as Postgres, MySQL, or similar systems, as well as Redis
• Understand indexing, query optimization, schema design, migrations, and database scalability concepts deeply
• Have experience supporting production systems with meaningful operational complexity
• Think beyond individual queries and into systems, workflows, maintainability, and reliability
• Can build tooling, automation, or operational improvements proactively
• Can show things you’ve built yourself: database tooling, performance optimization work, automation scripts, side projects, GitHub projects, or internal infrastructure work
• Are curious about how AI changes how engineering and operational workflows get built
• Experience with Postgres functions, PostGIS, and triggers is a plus

We use AI-assisted development workflows daily as part of our core infrastructure. We’re looking for engineers who’ve already started building their own workflows and can demonstrate:

• A project where AI assistance measurably changed your engineering workflow or speed
• How you support AI workflows with scripts, validation systems, observability, or structured context
• Knowledge of how to feed context and operational constraints into AI systems effectively
• A workflow you built to validate AI-generated outputs
• Situations where AI failed confidently and how you built safeguards around it

We want engineers who understand where AI accelerates workflows and where human judgment still matters.

You’ll probably enjoy this role if you:

• Like solving new, sometimes ambiguous systems problems and prefer building over excessive meetings
• Enjoy improving infrastructure and operational workflows
• Have built or optimized systems without being told exactly what to do
• Care deeply about performance, reliability, and maintainability
• Want real ownership of what you build

Our team works across modern backend and infrastructure technologies and is constantly experimenting with better tools and workflows. Current and emerging technologies include:

• Postgres / Ruby / Rails / Redis
• SQL-heavy operational workflows and AI-assisted development workflows
• Redis feature stores supporting low-latency API response
• Modern cloud infrastructure and CI/CD and automated testing systems
• Performance observability and operational tooling

We’re far more interested in how you solve problems than whether you’ve used a specific tool or framework.

• Early-stage fintech with real momentum and VC-backing by Tandem Ventures (Founders of fintech unicorns Divvy, Finicity, etc.) Small team, high ownership.
• Work on meaningful ecommerce and payments infrastructure and build alongside founders and experienced operators in a five-days-a-week in-office culture
• Opportunity to help shape the long-term data architecture and operational scalability of the platform
• Competitive compensation and benefits package including enterprise-level medical, dental, vision, 401(k), and generous time off