RemoteListed Jul 18, 2026
AI Engineer - Europe only
Talentuch
- AI-Development-Engineer
- AI-Engineer
- AI-Engineering-Jobs
- AI-Engineering-Specialist
- AI-ML-Engineer
- Artificial-Intelligence-Engineer
- Artificial-Intelligence-Engineer-Jobs
- Backend-Engineer
- Data Science
- LLM-Engineer
- ML-Platform-Engineer
- Machine-Learning-Engineer
- Remote-AI-Engineer
- Senior-AI-Engineer
Assessed from original listing evidence
The role
Job description
We’re looking for an AI Engineer to build the LLM layer of our platform: multi-agent workflows, hybrid retrieval over knowledge graphs and vector indexes, inference integration, and evaluation.
You’ll sit between research and platform — taking agent architectures from prototype to production and making them measurably reliable.
Your role
- Build and productionize multi-agent workflows on Anthropic/OpenAI APIs: orchestration, tool use, structured outputs, guardrails.
- Design hybrid retrieval architectures that combine knowledge graphs, vector search, and ranking into a single coherent context layer.
- Build evaluation harnesses and observability for agent behavior — quality, latency, cost — and use them to drive iteration.
- Integrate LLM inference, retrieval, and reasoning services into production backends.
- Work with researchers and domain experts to turn neuro-symbolic prototypes into robust product features.
What you’ll need
- 4+ years of software engineering experience (backend or ML), including production systems in Python.
- Hands-on experience building LLM systems beyond demos: agents and tool use, RAG, or evaluation pipelines.
- Real workflow experience with the OpenAI/Anthropic APIs (or comparable).
- Solid engineering fundamentals: API design, services, testing, deployment.
Nice to have
- Structured knowledge representations: ontologies, knowledge graphs, SPARQL, or graph databases (e.g., Neo4j).
- Vector databases and hybrid retrieval architectures.
- Kubernetes and cloud-native deployment.
- Model serving (e.g., vLLM), fine-tuning, or evaluation frameworks.
- Go and/or Scala.
Originally posted on Himalayas
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