AI Engineer - Europe only
Summary
Build and productionize multi-agent LLM workflows, hybrid retrieval systems, and evaluation pipelines using Anthropic/OpenAI APIs and Python, integrating them into scalable backend services.
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