# Cpl (client undisclosed) — Senior Lead AI Engineer (Agentic AI)

| Field | Value |
|---|---|
| **Date found** | 2026-05-21 |
| **Company** | Cpl (client undisclosed) |
| **Role** | Senior Lead AI Engineer (Agentic AI) |
| **Location** | Dublin, Hybrid |
| **Salary** | Undisclosed (competitive salary + bonus + benefits) |
| **Job URL** | [LinkedIn](https://www.linkedin.com/jobs/view/4411732846/) |
| **Status** | Closed |

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## Company Research

Recruiting agency — client undisclosed.

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## Job Summary

**What they do:** Cpl is recruiting for an undisclosed client building enterprise-scale AI-driven platforms and agentic systems.

**The role:** Senior Lead AI Engineer leading end-to-end design and delivery of multi-agent systems and AI orchestration at enterprise scale.

**Core work:**
- Design and build enterprise-scale AI and multi-agent systems with fault-tolerant orchestration
- Implement AI safety, guardrails, and evaluation frameworks; drive best practices in prompt engineering
- Mentor engineers and provide technical leadership across AI initiatives; evaluate emerging AI technologies

**Stack:** Python · agent-based frameworks · vector databases · Docker · Kubernetes · IaC

**Work style:** Hybrid, Dublin (on-site frequency unspecified); permanent role

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## Score: 62%

| Dimension | Score | Justification |
|---|---|---|
| Agentic AI depth (25%) | 75% | Multi-agent systems, orchestration, and guardrails are core; MCP only listed as nice-to-have |
| Tech fit (25%) | 65% | Python + agent frameworks, vector DBs, Docker/K8s; no explicit LangGraph/LangChain/CrewAI or LLM API names |
| Remote fit (25%) | 50% | Hybrid Dublin, on-site frequency unspecified; assumed standard 2 days/week |
| Company culture fit (15%) | 50% | Client anonymous — actual culture and domain unknown; cannot assess AI-nativeness |
| IC/leadership balance (10%) | 65% | IC + significant leadership/mentoring; "proven track record of leading projects or teams" required |
| **Final (weighted)** | **62%** | Solid agentic match offset by unknown client and hybrid uncertainty |

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## Strengths

- "Agentic AI" explicit in title and throughout JD — client knows exactly what they want
- MCP listed as nice-to-have — aligns with Luca's toolchain
- Fenergo alumni contact (Shauna Dalton, Cpl recruiter) — warm intro available
- AI safety and guardrails experience from prior roles is a direct fit

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## Weaknesses & Risks

- Client completely anonymous — actual product, culture, and tech stack depth unknown
- Salary undisclosed; "competitive" is vague — must ask early
- "Proven track record of leading technical projects or teams" skews toward management
- Hybrid on-site frequency unconfirmed; must clarify before investing time

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## Suggestions

- Contact Shauna Dalton (Fenergo alumni, Cpl) for warm intro and to find out the client company
- Ask Cpl to reveal the client before formal interview commitment
- Emphasise multi-agent system production experience and AI guardrails/safety work
- Clarify hybrid expectations upfront — target ≤2 days/week

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## Interview Tracker

| Stage | Date | Notes |
|---|---|---|
| Closed | 2026-05-22 | Posting removed — no longer accepting applications |
| Applied | | |
| Recruiter screen | | |
| Technical interview | | |
| Final round | | |
| Offer / Outcome | | |