• Act as a technical leader for multiple functional pods • Provide technical guidance, architectural direction, and hands-on assistance • Guide projects from planning through delivery, including attending project meetings • Write production code and implement key parts of the system • Support other engineers and unblock delivery • Contribute to improving on-call and production support practices

• Design, build, deploy, and maintain highly resilient and scalable features across Toast’s enterprise management products. Hands-on design and implementation experience in Java or Kotlin. • Lead complex projects that improve functionality and reliability for our customers • Partner with a wide array of teams across Toast • Ensure quality by building automated testing for changes • Roll features out to customers, including monitoring for success • Collaborate with UX and PM on the definition and design of features • Mentor and coach other engineers

• Deliver features end-to-end across our TypeScript/Node.js stack • Work on greenfield projects requiring creative, first-principles thinking • Build AI-powered features including chat, content generation, personalisation, and moderation • Leverage AI coding tools such as Cursor, Claude Code, and Copilot to accelerate development • Experiment with LLMs, embeddings, and AI integrations within product workflows • Ship quickly, iterate based on feedback, and learn from production • Collaborate closely with Product, Design, and senior engineers • Contribute to technical discussions and engineering standards

• Design, develop, and maintain AI-powered features and integrations across our platform, leveraging AWS Bedrock and related AWS AI/ML services. • Evaluate and select appropriate foundation models for specific business problems such as document analysis, intelligent matching, text extraction, and workflow automation. • Write maintainable, scalable, and well-tested code that integrates AI capabilities into existing application workflows. • Build and optimize prompt engineering strategies, retrieval-augmented generation (RAG) pipelines, and other techniques to maximize model accuracy and reliability. • Analyze, diagnose, and modify existing software to correct errors, adapt to new workflows, or improve performance. • Collaborate with product managers and stakeholders to identify processes that can benefit from AI automation and determine feasibility within time and cost constraints. • Establish best practices for AI integration including monitoring, cost management, evaluation frameworks, and responsible AI usage. • Work with other team members to create and evaluate estimates for development efforts based on stakeholder requirements. • Aid testers and support personnel as needed to troubleshoot the root cause of system issues. • Stay current with developments in AI/ML, foundation models, and AWS AI services, and advocate for their adoption where appropriate. • Additional responsibilities as assigned.