# Toast — Principal Software Engineer - AI Pod

| Field | Value |
|---|---|
| **Date found** | 2026-06-07 |
| **Company** | Toast |
| **Role** | Principal Software Engineer - AI Pod |
| **Location** | Dublin, Ireland (Hybrid — frequency unspecified) |
| **Salary** | Undisclosed |
| **Job URL** | [linkedin.com/jobs/view/4423539281](https://www.linkedin.com/jobs/view/4423539281/) |
| **Status** | New |

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## Company Research

| Field | Value |
|---|---|
| **Headquarters** | Boston, Massachusetts, USA |
| **Founded** | 2011 |
| **Employees** | ~7,600 (7,083 on LinkedIn) |
| **LinkedIn** | [company/toast-inc](https://www.linkedin.com/company/toast-inc/) — 318k followers |
| **Website** | [toasttab.com](https://www.toasttab.com) |
| **Blog** | [careers.toasttab.com](https://careers.toasttab.com) |

- **Product:** All-in-one POS and restaurant management platform — hardware, software, AI, and financial technology for restaurants and retailers.
- **Customers:** 164,000+ restaurant and retail locations globally; full range from independent restaurants to large chains.
- **Notable:** NYSE-listed (TOST), $27B+ market cap at peak; Dublin office is a key engineering hub; 3 Fenergo alumni and 1 Bologna alumni on team.

Indeed rating: 3.7/5 (culture 3.7, WLB 3.8)

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## Job Summary

**What they do:** Toast builds the operating system for restaurants — POS, payments, and now an AI-native engineering pod solving cross-cutting problems across the product.

**The role:** ⚠️ Principal Software Engineer in Toast's AI Pod — full-stack IC owning architecture and delivery of LLM-powered agent systems, MCP integrations, and AI-native tooling.

**Core work:**
- Architect and ship LLM-powered agents, tools, and workflows bringing AI into product and platform contexts
- Lead full-stack design: backend services (Java/Kotlin), frontend/developer interfaces (TypeScript/React)
- Set engineering standards and mentor engineers; serve as technical voice in cross-team architecture discussions

**Stack:** Java · Kotlin · TypeScript · React · LLM APIs · MCP (Model Context Protocol) · Claude Code · A2A protocols · LangFuse · DataDog

**Work style:** Hybrid Dublin, in-office frequency unspecified; Toast standard policy is "at least three days per week" per careers page — verify before applying.

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## Score: 62%

| Dimension | Score | Justification |
|---|---|---|
| Agentic AI depth (25%) | 75% | AI Pod explicitly builds LLM-powered agents, MCP integrations, A2A protocols, and agentic tooling — genuine agentic AI infrastructure scope. |
| Tech fit (25%) | 60% | MCP ✓, LLM agents ✓, Claude Code ✓, A2A ✓; Java/Kotlin is primary backend language (significant gap), TypeScript/React frontend expected; Python not mentioned. |
| Remote fit (25%) | 55% | Hybrid Dublin, frequency unconfirmed; Toast standard is 3 days/week which would fail the ≤2/month filter — must confirm before applying. |
| Company culture fit (15%) | 50% | Large NYSE-listed company (7,600 employees); AI Pod is an innovative sub-team but surrounded by enterprise restaurant-tech culture. Not AI-native. |
| IC/leadership balance (10%) | 70% | IC engineering with mentoring signals — "mentor engineers through design reviews, code reviews, and pairing." |
| **Final (weighted)** | **62%** | No salary deduction (undisclosed). Main risk: hybrid office frequency and Java/Kotlin gap. |

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## Strengths

- AI Pod is Toast's dedicated AI-native engineering team — building agents, MCP, A2A protocols
- Only 5 applicants at time of posting — very early, low competition
- MCP, A2A, and agentic agent tooling align with Luca's current specialisation
- 3 Fenergo alumni and 1 Bologna school alum (Allyson Bonneau Rivas) — potential warm intro network
- Claude Code explicitly mentioned in JD ("AI coding assistants e.g. Claude Code")

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## Weaknesses & Risks

- ⚠️ Hybrid office frequency ambiguous — Toast standard is 3 days/week which would fail hard filter; must confirm remote-first option for Dublin
- Primary backend is Java/Kotlin — major gap for Luca (Python/AI stack)
- TypeScript/React frontend expected — another gap
- Large company (7,600 employees) with restaurant-tech culture — low AI-native culture score
- Salary undisclosed — large company may cap below €130k+ target

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## Suggestions

- Confirm hybrid policy before applying: ask if remote-first is possible for this role
- Reach out to Fenergo alumni at Toast for a warm intro
- Emphasise MCP experience (Fenergo agentic pipeline, Claude Code usage), A2A knowledge, and LLM agent architecture
- Acknowledge Java/Kotlin gap proactively — Luca's Python/AI background is the primary value add, not the backend language

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## Interview Tracker

| Stage | Date | Notes |
|---|---|---|
| Applied | | |
| Recruiter screen | | |
| Technical interview | | |
| Final round | | |
| Offer / Outcome | | |