Описание
The company is an AI SaaS and Developer Tools business based in Berlin. It develops LLM infrastructure that enables engineering teams to deploy, evaluate, observe, and operate LLM-powered applications at scale.
Задачи
- Build platform services for production LLM applications
- Develop model gateways and APIs for accessing multiple LLM providers
- Build shared RAG and vector retrieval infrastructure
- Develop Python tooling and services for AI engineering teams
- Deploy and operate AI workloads on Kubernetes
- Build evaluation pipelines for LLM and RAG applications
- Implement observability across prompts, models, retrieval, latency, cost, and failures
- Automate infrastructure and environments using Terraform
- Create deployment tooling and self-service capabilities for engineering teams
- Improve reliability, scalability, and operational standards across production AI applications
Требования
- 4+ Years in Platform Engineering, AI Engineering, MLOps, Backend Engineering, or similar roles
- Strong understanding of production cloud-native systems
- Nice to have: OpenAI, Anthropic, or multiple model providers, Pinecone, Weaviate, Qdrant, or pgvector, LangGraph / LangChain, LLM gateways or routing platforms, OpenTelemetry, LLM evaluation and tracing tools, AWS / GCP, GitOps / Argo CD, Model Context Protocol (MCP), experience building internal developer platforms
Условия
Berlin, Germany.
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