Senior Principal Software Engineer - AI Pod

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

Senior Principal Software Engineer and Architect for an AI Pod at Toast, focusing on setting technical vision and architectural direction for AI-native development, including LLM-powered agents and agentic systems. The role requires hands-on experience in building, deploying, and operating these systems, as well as evolving agentic development practices.

What you'd actually do

  1. Develop and drive the architectural vision for AI Pod, establishing patterns for AI-native development that scale across Toast engineering
  2. Be an active participant and authoritative technical voice in cross-organizational strategy and architecture discussions
  3. Lead the pod's most complex, high-impact initiatives from design through production — staying hands-on throughout
  4. Evolve agentic development practices within the pod and champion their adoption across Toast
  5. Work closely with other Senior Principal Engineers and technical leaders across Toast to advance the overall architecture

Skills

Required

  • 12+ years of experience designing and building highly scalable, mission-critical distributed software systems
  • 10+ years of experience building and operating SaaS products, ideally AWS-hosted
  • Demonstrated ability to drive architectural vision for a company, line of business, or highly scalable platform
  • Deep experience building, deploying, and operating LLM-powered agents and AI-native systems
  • 1+ years of hands-on experience using the latest AI coding agents with a strong desire to go all-in on agentic development practices
  • Experience with MCP (Model Context Protocol), tool use patterns, or similar agentic integration frameworks
  • Ability to move fluidly between whiteboard architecture and understanding the ebb and flow of code under load
  • Ability and desire to communicate and influence at the executive level

Nice to have

  • Experience managing or leading a small engineering team (2-4 engineers)
  • Familiarity with A2A (Agent-to-Agent) protocols and multi-agent orchestration patterns
  • Experience with machine learning concepts, model evaluation, or ML infrastructure
  • Familiarity with observability tooling for AI/LLM systems (e.g., Langfuse, DataDog)

What the JD emphasized

  • Deep experience building, deploying, and operating LLM-powered agents and AI-native systems
  • 1+ years of hands-on experience using the latest AI coding agents with a strong desire to go all-in on agentic development practices
  • Experience with MCP (Model Context Protocol), tool use patterns, or similar agentic integration frameworks

Other signals

  • AI-native engineering team
  • LLM-powered agents
  • agentic development practices