# Jobgether (partner undisclosed) — AI Research Engineer (Agentic Post-training)

| Field | Value |
|---|---|
| **Date found** | 2026-05-21 |
| **Company** | Jobgether (partner company undisclosed) |
| **Role** | AI Research Engineer (Agentic Post-training) |
| **Location** | Ireland, Remote |
| **Salary** | Undisclosed |
| **Job URL** | https://www.linkedin.com/jobs/view/4416382886/ |
| **Status** | New |

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## Company Research

Recruiting agency (Jobgether) — partner company undisclosed.

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## Job Summary

**What they do:** Partner company undisclosed — described as a cutting-edge AI research company at the intersection of multimodal learning, distributed training, and autonomous agents.

**The role:** AI Research Engineer — frontier LLM post-training research focused on advancing agentic AI systems.

**Core work:**
- Research post-training methods: tool use, multi-step reasoning, function calling, multi-agent coordination
- Build large-scale training and evaluation pipelines
- Produce research with direct impact on production-grade AI deployed on cloud and edge

**Stack:** Python · PyTorch · distributed training · LLMs · evaluation harnesses

**Work style:** Fully remote, global

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## Score: 79%

| Dimension | Score | Justification |
|---|---|---|
| Agentic AI depth (25%) | 90% | Frontier post-training for agentic systems: tool use, multi-step reasoning, autonomous behaviour — this IS the core of agentic AI work |
| Tech fit (25%) | 60% | PyTorch, distributed training, LLMs — strong ML infrastructure fit; no explicit LangGraph/LangChain/CrewAI mention, more research-side |
| Remote fit (25%) | 100% | Fully remote, globally distributed |
| Company culture fit (15%) | 50% | Unknown partner company — could be AI-native lab or larger org; upside and downside both present |
| IC/leadership balance (10%) | 85% | Hands-on research/engineering IC; collaboration with teams but no people management implied |
| **Final (weighted)** | **79%** | |

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## Strengths

- Genuinely frontier agentic AI research (post-training, tool use, reasoning) — highest possible AI depth
- Fully remote, Ireland-based posting
- Strong alignment with Luca's agentic AI systems background
- 19 applicants at time of discovery — low competition window

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## Weaknesses & Risks

- Real employer is hidden — need to invest in process before knowing who the company is
- Role likely expects publications/research track record (PhD strongly preferred)
- Tech stack skews more research/training (distributed, multimodal) than applied agentic engineering (LangGraph, CrewAI)
- Jobgether's AI-mediated matching process may filter before human review

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## Suggestions

- Apply via Jobgether Easy Apply to enter their pipeline; the real company will be revealed if shortlisted
- Highlight any LLM fine-tuning, RLHF, or evaluation framework experience from past roles
- Emphasise agentic system design and multi-agent orchestration work as applied counterpart to the research focus

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## Interview Tracker

| Stage | Date | Notes |
|---|---|---|
| Rejected | 2026-05-25 | Too high skills (publications, research) |
| Applied | | |
| Recruiter screen | | |
| Technical interview | | |
| Final round | | |
| Offer / Outcome | | |