Principal Software Engineer (dublin, Ireland)

Toast · Enterprise · Dublin, Ireland · R & D : Cloud Service Infra

Toast is seeking a Principal Software Engineer to lead full-stack design and delivery of AI-native solutions, focusing on building and integrating LLM-powered agents, tools, and workflows. The role requires strong experience in scalable software systems, technical architecture, and LLM agent development, with a focus on enterprise AI applications within the restaurant technology sector.

What you'd actually do

  1. Lead full-stack design and delivery of AI-native solutions that address complex, cross-functional problems across Toast
  2. Drive technical architecture for pod initiatives, from backend services and APIs to frontend and developer-facing interfaces
  3. Build and integrate LLM-powered agents, tools, and workflows that bring AI capabilities directly into product and platform contexts
  4. Set and uphold engineering standards within the pod: code quality, system design, testing, and operational practices
  5. Mentor engineers through design reviews, code reviews, and pairing

Skills

Required

  • 10+ years of experience designing and delivering scalable software systems
  • strong full-stack background spanning backend services and frontend or developer-facing interfaces
  • Demonstrated experience leading technical architecture for a platform, product, or engineering team
  • Experience building, deploying, or operating LLM-powered agents or AI platform infrastructure
  • Familiarity with AI coding assistants (e.g., Claude Code, Cursor, GitHub Copilot) and experience extending them through custom plugins, skills, or hooks
  • Experience with MCP (Model Context Protocol), tool use patterns, or similar agentic integration frameworks
  • Strong prompt engineering skills and intuition for how LLM behavior responds to context and instructions
  • Strong foundation in modern backend (Java, Kotlin, or similar) and frontend (TypeScript, React, or similar) technologies
  • A bias towards action and comfort operating in ambiguous, rapidly evolving problem spaces

Nice to have

  • Familiarity with A2A (Agent-to-Agent) protocols and multi-agent orchestration patterns
  • Experience with machine learning concepts, model evaluation, or ML infrastructure
  • Experience building developer experience platforms or internal tooling
  • Familiarity with observability tooling for AI/LLM systems (e.g., Langfuse, DataDog)

What the JD emphasized

  • Experience building, deploying, or operating LLM-powered agents or AI platform infrastructure
  • Experience with MCP (Model Context Protocol), tool use patterns, or similar agentic integration frameworks
  • Strong prompt engineering skills

Other signals

  • LLM-powered agents
  • AI platform infrastructure
  • agentic integration frameworks
  • prompt engineering