# Cpl (undisclosed client) — Senior Applied AI Engineer – Generative & Agentic AI

| Field | Value |
|---|---|
| **Date found** | 2026-05-20 |
| **Company** | Cpl (recruiter) / end client undisclosed |
| **Role** | Senior Applied AI Engineer – Generative & Agentic AI |
| **Location** | Dublin, Hybrid (frequency undisclosed) |
| **Salary** | Undisclosed |
| **Job URL** | https://www.linkedin.com/jobs/view/4411732848/ |
| **Status** | Closed |

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## Company Research

Recruiting agency (Cpl) — end client undisclosed.

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## Job Summary

**What they do:** End client undisclosed — described as a major organisation with a "global AI Innovation and R&D team."

**The role:** Senior IC building production-grade agentic AI systems end-to-end, placed by Cpl staffing agency.

**Core work:**
- Build stateful agentic workflows: planning, tool use, memory, human-in-the-loop
- Design advanced retrieval pipelines: hybrid search, reranking, vector store management
- Implement LLMOps/AgentOps monitoring and evaluation
- Integrate agent systems with backend services

**Stack:** Python · LangChain · LangGraph · CrewAI · vector DBs · Docker · AWS/Azure

**Work style:** Hybrid, Dublin (on-site frequency unspecified) — requires Stamp 1G / Stamp 4 / EU work rights

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## Score: 73%

| Dimension | Score | Justification |
|---|---|---|
| Agentic AI depth (25%) | 90% | Near-perfect agentic AI match: stateful agents, planning, tool use, multi-agent patterns, LLMOps/AgentOps. This describes exactly the type of work Luca does. |
| Tech fit (25%) | 90% | Exceptional stack alignment: LangChain, LangGraph, CrewAI ✓, Python ✓, RAG/vector DBs ✓, AWS/Azure ✓, Docker ✓, LLMOps ✓. Very few gaps. |
| Remote fit (25%) | 50% | Hybrid Dublin. On-site frequency not stated — "commutable distance" implies regular office visits. Risk of exceeding 1–2 times/month. Flag before progressing. |
| Company culture fit (15%) | 40% | End client is unknown — impossible to assess culture, stage, or company type. Cpl as intermediary adds opacity. |
| IC/leadership balance (10%) | 90% | Clearly IC-focused, hands-on building and delivery. No management implied. |
| **Final (weighted)** | **73%** | |

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## Strengths

- Tech stack match is among the best possible: LangChain/LangGraph/CrewAI explicitly listed
- Agentic AI work description matches Luca's experience almost point-for-point
- AgentOps/LLMOps focus aligns with Luca's MLOps background
- Dublin-based: removes relocation risk, familiar market
- 6+ years requirement is easily met

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## Weaknesses & Risks

- **End client is anonymous** — major unknown; culture, stage, domain, and company health cannot be assessed until the recruiter reveals the client
- **Hybrid frequency unspecified** — could easily be 3 days/week, which would fail the location hard filter; must clarify before proceeding
- Salary undisclosed — needs to be verified ≥ €100k filter, ≥ €110k preference
- Cpl is a large staffing agency; recruitment experience may be transactional

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## Suggestions

- Contact Cpl recruiter (James Monks per LinkedIn) immediately to ask two questions before anything else: (1) who is the end client?, (2) what is the on-site frequency?
- If client is an AI-native company and remote flexibility confirmed, this jumps to top-tier
- Lead application with LangGraph/CrewAI/LangChain experience — it's what they explicitly want
- Highlight Fenergo agentic pipeline + cybersecurity multi-agent platform as direct production examples

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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 | | |