Responsibilities
- Turn ambiguous product and operational workflows into well-structured systems combining data pipelines, backend services, and AI-driven logic
- Design and build agentic AI systems that reason, take actions, and orchestrate multi-step workflows (not just simple LLM integrations)
- Develop and operate production-grade data pipelines powering both user-facing features and internal systems
- Build backend services primarily in TypeScript, with pragmatic use of Python where appropriate
- Design APIs and system boundaries that enable modular, composable AI and data workflows
- Partner with product and operations to translate real-world processes into AI-augmented, scalable systems
- Use AI-assisted development as a default—from prototyping to debugging to system design
- Improve reliability, observability, and performance across services
- Own architectural decisions within your domain, balancing speed and long-term maintainability
Requirements
- Proven experience owning and operating data-heavy systems in production
- Strong experience with data pipelines (ETL/ELT, event-driven, or workflow-based systems)
- Proficiency in TypeScript (primary language); other typed language experience is a plus
- Generalist mindset with strong data modeling and system design instincts
- Ability to go from zero → one → scale with minimal guidance
- You actively use AI tools as a core part of your development workflow (not optional)
- You believe the software engineer’s job is fundamentally changing—and you lean into that shift
Nice to Have
- Experience in fintech, tax, or regulated environments a strong plus
- Familiarity with security and compliance considerations (sensitive data, auditability, access controls) a strong plus
