# Scorebuddy — AI Software Engineer

| Field | Value |
|---|---|
| **Date found** | 2026-05-24 |
| **Company** | Scorebuddy |
| **Role** | AI Software Engineer |
| **Location** | Dublin, Ireland (Hybrid) |
| **Salary** | Undisclosed |
| **Job URL** | https://www.linkedin.com/jobs/view/4415568569/ |
| **Status** | New |

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## Company Research

| Field | Value |
|---|---|
| **Headquarters** | Dublin, Ireland |
| **Founded** | — |
| **Employees** | 51–200 (60 total; 60 on LinkedIn) |
| **LinkedIn** | https://www.linkedin.com/company/scorebuddy/ — 6.3k followers |
| **Website** | https://www.scorebuddy.com |
| **Blog** | — |

- **Product:** Quality Management SaaS platform for contact centres — AI-powered call/interaction scoring, agent coaching, and analytics.
- **Customers:** Contact centre teams globally, from 20 to 20,000 end users.
- **Notable:** Profitable SaaS with diverse international customer base; AI squad already shipping production ML/LLM features; growing engineering team.

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## Job Summary

**What they do:** Scorebuddy is a contact centre QA SaaS platform that uses AI to automate quality scoring, coaching, and analytics.

**The role:** AI Software Engineer within the AI squad, building and shipping production NLP/LLM features for quality assurance workflows.

**Core work:**
- Build, integrate, and fine-tune LLM pipelines and NLP workflows (classification, NER, summarisation, embeddings, RAG) for production
- Train and deploy Hugging Face Transformer models (BERT-family) for downstream NLP tasks
- Design and maintain scalable backend AI services on AWS with Python

**Stack:** Python · HuggingFace Transformers · LangChain · LlamaIndex · Anthropic API · OpenAI API · AWS · RAG · Docker · Kubernetes

**Work style:** Dublin city hybrid; on-site frequency unspecified. Role requires office presence.

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## Score: 48%

| Dimension | Score | Justification |
|---|---|---|
| Agentic AI depth (25%) | 25% | Core work is NLP/LLM pipelines for contact centre QA — no agentic orchestration, multi-agent systems, or autonomous workflows. LangChain is listed as a tool to evaluate rather than the primary architecture. |
| Tech fit (25%) | 65% | Strong Python/AWS fit; HuggingFace, LangChain, Anthropic API in stack. No LangGraph or multi-agent frameworks. |
| Remote fit (25%) | 40% | Dublin Hybrid with unspecified frequency — likely 2–3 days/week based on "modern offices" emphasis. |
| Company culture fit (15%) | 45% | Small AI-native SaaS startup (60 people) in QA domain. Lean culture but contact centre focus is niche. |
| IC/leadership balance (10%) | 85% | Pure IC engineering role with sound ownership signals. |
| **Final (weighted)** | **48%** | |

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## Strengths

- Small AI squad already in production — real AI engineering, not greenfield proof-of-concepts
- Anthropic API and LangChain in tech stack align with Luca's toolchain
- HuggingFace Transformers experience maps to Luca's audio/NLP background
- Small company = high IC ownership and influence over AI architecture

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## Weaknesses & Risks

- Very low agentic AI depth — this is NLP engineering for call QA, not agent orchestration
- Dublin Hybrid with unclear frequency — risk of frequent on-site requirement
- Salary undisclosed, small company — likely below €110k target
- Contact centre domain is niche and not aligned with Luca's agentic AI focus

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## Suggestions

- Apply only if hybrid frequency is ≤2 days/month and salary is verified at €110k+
- Clarify on-site expectations before investing time — small company may have undefined hybrid policy

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## Interview Tracker

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