Toast

Staff Software Engineer for Toast's AI Foundations team, focusing on building core AI platform infrastructure like LLM Proxy and observability pipelines, as well as architecting and delivering autonomous agents for the SDLC. The role involves leading technical design, driving adoption of agentic practices, and mentoring engineers.

This role focuses on building and deploying AI-powered tools and automation workflows within an enterprise risk management program. Key responsibilities include developing risk dashboards, administering risk management systems, and specifically designing, building, testing, and deploying AI tools such as automated risk assessment assistants and LLM-based workflows. The role requires experience with Generative AI for process automation and data analysis.

Senior Software Engineer on Toast's AI Foundations team, building internal AI platform infrastructure including LLM proxy, agentic workflows, and a plugin marketplace to enable AI-native development practices across the company.

Machine Learning Engineer II at Toast, focusing on building and deploying scalable ML and agentic AI pipelines, developing APIs, and implementing microservices with a focus on latency, reliability, and performance. The role involves MLOps best practices, model deployment, orchestration, and monitoring, working closely with cross-functional teams to deliver ML-powered products.

Senior Data Scientist at Toast, focusing on end-to-end development and production deployment of agentic AI workflows and ML solutions within the fintech domain. Requires strong engineering mindset, Python/SQL proficiency, and experience with modern ML techniques.

Lead Analyst role at Toast Capital focusing on designing and deploying AI-powered workflows for credit risk functions. The role involves identifying opportunities to improve underwriting, portfolio monitoring, and risk operations by implementing internal AI tools like copilots and assistants, leveraging structured data and LLM platforms. Requires strong credit risk intuition, analytical skills, and technical curiosity in AI and automation.

This role focuses on managing model risk for AI/ML models, particularly fraud detection and Generative AI systems, within a fintech company. Responsibilities include model validation, risk assessment, ensuring adherence to the Model Risk Management program, and staying updated on regulatory guidance. The role requires a strong understanding of ML methodologies, fraud analytics, and GenAI risks.

Staff Machine Learning Engineer to design and lead the evolution of a unified MLOps platform supporting diverse needs across Toast, ensuring high availability, scalability, and security of ML services. This role involves championing MLOps best practices, leading collaborative efforts between Data Engineering, DevOps, and Product teams, defining technical vision for AI infrastructure, setting standards for observability and incident response for ML systems, and mentoring engineers.