# Mastercard — Agentic AI Senior Software Engineer

| Field | Value |
|---|---|
| **Date found** | 2026-05-20 |
| **Company** | Mastercard (Foundry R&D) |
| **Role** | Agentic AI – Senior Software Engineer |
| **Location** | Dublin, Hybrid (frequency undisclosed) |
| **Salary** | Undisclosed (Fortune 500 — likely competitive) |
| **Job URL** | https://www.linkedin.com/jobs/view/4402836125/ |
| **Status** | New |

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## Company Research

| Field | Value |
|---|---|
| **Headquarters** | Purchase, New York, USA (global HQ); Dublin, Ireland (European Tech Hub & Foundry R&D HQ) |
| **Founded** | 1966 |
| **Employees** | 10,000+ globally; ~1,000 in Dublin (49,143 on LinkedIn) |
| **LinkedIn** | [company/mastercard](https://www.linkedin.com/company/mastercard/) — 2M followers |
| **Website** | [mastercard.com](https://www.mastercard.com) |
| **Blog** | [mastercard.com/news](https://www.mastercard.com/news/) |

- **Product:** Global digital payments network processing billions of transactions daily; Mastercard Foundry is its internal R&D and innovation arm
- **Customers:** Banks, merchants, governments, and consumers across 210+ countries
- **Notable:** Dublin European Tech Hub (opened 2022) is Foundry R&D's global HQ, focused on payments security, APIs, emerging tech, and AI

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## Job Summary

**What they do:** Mastercard Foundry R&D is an internal innovation team building reusable AI tooling, patterns, and developer-facing capabilities to accelerate AI adoption across Mastercard globally.

**The role:** Hands-on agentic AI engineer in the Dublin Foundry — building internal AI applications, prototypes, and platforms.

**Core work:**
- Build agentic AI applications and evaluate models and frameworks
- Create developer experience tooling for internal AI adoption
- Full-stack work spanning Python/Java backend and React/Next.js frontend
- Collaborate with cross-functional stakeholders to drive adoption

**Stack:** Python · Java · React/Next.js · LLMs · agentic frameworks

**Work style:** Hybrid, Dublin (on-site frequency unspecified; Mastercard standard is 3 days/week — must verify)

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## Score: 60%

| Dimension | Score | Justification |
|---|---|---|
| Agentic AI depth (25%) | 78% | Real agentic AI work: building reusable agentic patterns, evaluating frameworks, prototyping. But framed as internal tooling/platform work rather than core AI product engineering. |
| Tech fit (25%) | 55% | Python ✓, LangGraph ✓, AWS ✓, agentic patterns ✓. Significant gaps: React/Next.js and Java are explicitly required — neither is in Luca's stack. This is a meaningful mismatch for a role that lists them as core requirements. |
| Remote fit (25%) | 45% | Hybrid Dublin. Mastercard is a large traditional corporate — likely standard 3-day hybrid. Frequency unconfirmed but risk is high of exceeding 1–2 on-sites/month. |
| Company culture fit (15%) | 50% | Foundry R&D is more innovative than standard Mastercard, but it's still a 30,000-person financial company. Process, security requirements, and corporate pace are real risks. |
| IC/leadership balance (10%) | 80% | IC-focused with stakeholder collaboration. No management implied. |
| **Final (weighted)** | **60%** | |

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## Strengths

- Mastercard Foundry R&D is a relatively autonomous innovation team within a large company
- Agentic AI focus with real product impact — not just internal tooling for its own sake
- Fortune 500 salary scale — likely meets or exceeds the €110k preference
- Dublin-based, no relocation risk
- Prototyping and experimenting with models/frameworks aligns with Luca's preferred day-to-day
- 100+ applicants but Luca has a direct Bologna alumni connection

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## Weaknesses & Risks

- **React/Next.js + Java required** — these are core listed requirements, not nice-to-haves. Luca's stack doesn't include either. This is the biggest risk.
- Hybrid on-site frequency likely to exceed 1–2 times/month for a large corporate
- Large financial company: security compliance requirements, slower decision-making, potential bureaucracy
- Internal tooling focus means impact is indirect (enabling others) rather than shipping AI products to external users

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## Suggestions

- Only pursue if the Java/React gap can be clearly positioned as learnable given Luca's 20+ years of SW engineering depth
- Clarify hybrid frequency early — if it's 3 days/week, this fails the hard location filter
- If progressing, lead with the Foundry-relevant angle: cross-team AI enablement, reusable agentic patterns, stakeholder problem-framing experience
- The Bologna alumni contact is worth a warm message before applying cold

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## Interview Tracker

| Stage | Date | Notes |
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| Applied | | |
| Recruiter screen | | |
| Technical interview | | |
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