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Senior GenAI / LLM Engineer (RAG, MLOps) at Test Triangle – Dublin 1 | Jobyssey

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Senior GenAI / LLM Engineer (RAG, MLOps)

Senior GenAI / LLM Engineer (RAG, MLOps)

Test Triangle · Dublin 1, Ireland · 3 months ago

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Seniority: Senior
Employment: Contract
Category: AI engineering
Experience: 1+ years

agentic-ai ai anthropic api argocd azure azure-devops ci-cd claude data-science devops

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Senior GenAI / LLM Engineer (RAG, MLOps)

Role: Senior Generative AI / LLM Engineer

Experience: 6–10 years (Apps Development / Systems Analysis / AI Engineering)

Location: Ireland

Type: Fixed term contract 1 year.

Must‑Have Skills

Strong foundations in GenAI, ML modeling, Data Science, Statistics, and AI fundamentals (NLP, Neural Networks, LLMs)
Hands‑on with major LLMs: Google Gemini, OpenAI, Anthropic Claude, Mistral, Llama + open‑source models
Critical: Deep, hands‑on experience building Retrieval‑Augmented Generation (RAG) pipelines (advanced RAG techniques + implementation)
Strong Prompt Engineering (prompt strategies, tuning, reusable templates) and agentic frameworks
Python (mandatory) with strong experience across: Pandas, NumPy, scikit‑learn, PyTorch/TensorFlow, Transformers, FastAPI, LangChain, LlamaIndex

Data / Integration

Experience integrating GenAI into enterprise apps using APIs, orchestration tools, and knowledge/graph concepts
Vector DB experience: PGVector, Pinecone, MongoDB Atlas, Neo4j (or similar)
Experience handling large‑scale unstructured data and high‑throughput processing

Deployment / MLOps

Critical: Proven experience deploying GenAI/LLM solutions to production
Strong MLOps knowledge: evaluation, monitoring, and robust deployment pipelines
CI/CD tools exposure: Jenkins, GitLab CI, Azure DevOps, ArgoCD
Container orchestration: Kubernetes or OpenShift

Other / Soft Skills

Strong problem solving, stakeholder collaboration, and ability to work independently on ambiguous problems
Working knowledge of Guardrails and methods to assess performance/safety of GenAI features