Staff Software Engineer, AI Pod

<p>Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.</p> <p>AI Pod is Toast's internal platform team for AI. We build… ## What you'll do )</strong></p> <ul> <li>Design, build, and ship core AI platform infrastructure, including the LLM proxy, AI key management, and observability pipelines powering Toast's internal AI ecosystem</li> <li>Architect and deliver autonomous agents that participate in the SDLC, including the AI Review GitHub App and Developer Platform MCP integrations</li> <li>Build on and help maintain the internal plugin marketplace, developing plugins that encode Toast's architectural standards, PR patterns, and quality practices directly into AI assistant behavior</li> <li>Lead technical design and implementation of MCP (Model Context Protocol) services and no-code service templates that accelerate AI-powered development across Toast</li> <li>Drive adoption of agentic development practices through tooling, internal evangelism, and hands-on enablement across engineering teams</li> <li>Mentor engineers through code reviews, architecture discussions, and pairing sessions</li> <li>Partner with product and platform teams to define and expand the AI Foundations roadmap</li> </ul> <p>&nbsp;</p> <p><strong>What you'll need to thrive ( ## What you'll bring )</strong></p> <ul> <li>8+ years of experience designing and implementing scalable backend services</li> <li>Strong foundation in Java, Kotlin, or another object-oriented language, with experience building scalable backend services</li> <li>Demonstrated experience building, deploying, or operating LLM-powered agents or AI-assisted developer tooling</li> <li>Deep familiarity with AI coding assistants (e.g., Claude Code, Cursor, GitHub Copilot) and the ability to extend them through custom plugins, skills, or hooks</li> <li>Hands-on experience with MCP (Model Context Protocol), tool use patterns, or agentic frameworks</li> <li>Strong prompt engineering skills and intuition for how LLM behavior changes with context, instructions, and tool definitions</li> <li>Proven track record of technical leadership: influencing architecture decisions, setting quality standards, and mentoring peers</li> <li>Experience with distributed systems, API design, and cloud-native infrastructure</li> <li>Strong customer empathy and the ability to translate developer pain points into platform solutions</li> </ul> <p>&nbsp;</p> <p><strong>What will help you stand out</strong></p> <ul> <li>Familiarity with A2A (Agent-to-Agent) protocols and multi-agent orchestration patterns</li> <li>Experience with machine learning concepts, model evaluation, or ML infrastructure</li> <li>Experience building developer experience platforms, internal tooling, or API gateways</li> <li>Familiarity with observability tooling for ### Ai/Llm …

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