AI Engineer
- Джерело:
- djinni.co
Що робити
- 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.
Що пропонуємо
- 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.
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