Principal Software Engineer

Toast Toast · Enterprise · Dublin, Ireland · R & D : Engineering : Team

Principal Software Engineer to lead architectural design and implementation of AI agents and infrastructure for Toast's Team area within their FinTech line of business. Responsibilities include defining technical architecture, partnering with product managers, hands-on coding, and mentoring engineers. Requires 10+ years of experience in distributed systems and SaaS products, with a strong enthusiasm for agentic development practices and LLM integration.

What you'd actually do

  1. Define and execute the technical architecture for AI agents within the Team domain, ensuring systems are scalable, reliable, and secure.
  2. Partner closely with Engineering Managers and Product Managers to translate product roadmaps into robust technical designs and deliverables.
  3. Maintain a strong hands-on presence, writing code, prototyping new patterns, and resolving complex technical bottlenecks under load.
  4. Collaborate with Principal and Senior Principal Engineers across Toast to align on best practices, agent patterns, and spec-driven development paradigms.
  5. Guide, mentor, and elevate engineers within the Team area, fostering a culture of technical excellence and continuous learning.

Skills

Required

  • 10+ years of experience designing, building, and operating highly scalable, mission-critical distributed systems and SaaS products
  • Proven track record of leading complex technical initiatives and delivering robust software architecture from design to production
  • Strong enthusiasm for agentic development practices, LLM integration, and modern software paradigms
  • Ability to design high-level technical solutions on a whiteboard while remaining deeply connected to code-level execution and system performance
  • Effective communication: Ability to articulate complex technical ideas clearly to both technical peers and product leadership

Nice to have

  • Experience building systems that leverage LLMs, autonomous agents, or ML models
  • Hands-on experience with enterprise integration frameworks (e.g., Apache Camel) or event-driven messaging systems (e.g., Apache Pulsar)
  • Experience establishing robust CI/CD, testing, and deployment strategies for complex systems
  • Domain knowledge in workforce management or restaurant operations

What the JD emphasized

  • AI agents
  • agentic workflows
  • LLM integration
  • agentic development practices

Other signals

  • AI agents
  • LLM integration
  • spec-driven development