Staff Software Engineer, Finance Automation

Toast creates technology to help restaurants and local businesses succeed in a digital world. Toast is seeking a hands-on Staff Software Engineer to transform AI prototypes into enterprise-grade backend microservices, data pipelines, and internal finance automation tools. The role also owns integrations, enterprise controls, and lightweight frontend operator tools for Finance teams.

Responsibilities:

• Hands-on Execution & Leadership: Spend the majority of your time "hands-on-keyboard," architecting, coding, and operating high-performance backend services using Kotlin and AWS
• Productionize AI Workflows: Take working agentic prototypes built by Finance operators and turn them into scalable, monitored, and permissioned microservices with audit trails and automated error handling
• End-to-End Internal Tooling: Build pragmatic, full-stack operator tools—from backend APIs and pipelines down to the lightweight UI surfaces used daily by collections analysts and revenue accountants to run and monitor automations safely
• Integration & Systems Architecture: Design resilient integrations across billing platforms, ERP systems, Salesforce, data warehouses, and internal Toast services using enterprise integration patterns
• Design for Enterprise Controls: Proactively engineer around SOX scope, PCI boundaries, and data access requirements alongside Security, Compliance, and Audit teams from day one
• Technical Ownership & Strategic Handoffs: Own end-to-end technical strategy from high-level business problems down to build sequencing. Recognize when fixes belong in core Toast platforms, driving technical cases and clean handoffs rather than duplicating capabilities

Requirements:

• Proven track record as a Staff (or senior-level lead) engineer with deep expertise in distributed backend systems, paired with the practical ability to ship frontend UI surfaces or admin portals when an internal tool requires it
• Advanced hands-on experience shipping Kotlin (or strong JVM equivalent) services on AWS, with deep familiarity in cloud-native backend patterns
• Practical experience productionizing LLM frameworks and agentic architectures (tool use, retrieval/RAG, evals, context management) paired with strong judgment on when an AI agent is required versus a traditional backend system or cron job
• Extensive experience with enterprise integration frameworks, message brokers, and distributed data stores—specifically Apache Camel, Apache Pulsar, DynamoDB, and Dropwizard (or direct equivalents)
• Advanced data engineering instincts across SQL, warehouse modeling, pipeline design, and managing data flow/consistency across relational and NoSQL storage systems
• Ability to balance immediate high-impact automation with long-term platform scalability, accompanied by exceptional technical writing that translates complex architectural trade-offs to executive stakeholders
• Extensive background in Fintech, revenue systems, automated reconciliation, or operating within strict SOX/PCI control environments
• Deep experience building internal platforms, administrative dashboards, or operator tooling for non-technical business users
• Prior experience embedded directly alongside finance, revenue, or business ops functions to solve core operational scaling challenges