Dream
Dream
Dream ir aizsardzības un mākslīgā intelekta uzņēmums, kas izstrādā mākslīgā intelekta platformu kibernoturībai. Tā tehnoloģija ir paredzēta, lai palīdzētu valdībām stiprināt valsts drošību, pārvēršot liela mēroga kiberdatus skaidrākā situācijas izpratnē, prognozējamā aizsardzībā un reāllaika draudu mazināšanā pret uzbrukumiem, kas saistīti ar naidīgām valstīm. Dream pievēršas datu problēmām, kuru dēļ mūsdienu kiberaizsardzība ir sarežģīta.

Senior Backend Engineer, Agentic AI — Hybrid in Israel

Build Python backend services and LLM agents for Dream’s sovereign AI and national cyber-defense platform. Design secure, scalable systems serving government customers.

Apraksts

  • Develop and run scalable Python backend services
  • Create and integrate LLM agents through prompt orchestration, tool and function calling, and agentic architecture patterns
  • Lead data modeling and database design for complex production systems
  • Integrate backend and AI capabilities with user-facing applications
  • Containerize and deploy services in AWS environments
  • Create automated tests and CI pipelines for dependable, rapid delivery
  • Apply secure software development practices, including secret management, dependency hygiene, and rigorous code reviews
  • Own systems from technical design through production operations

Prasības

  • At least four years of hands-on experience developing production Python backend services
  • Strong command of modern Python frameworks, ideally asynchronous frameworks such as FastAPI
  • Demonstrated production experience building or integrating LLM agents, including prompt orchestration, tool or function calling, and agentic architectures
  • Practical expertise in data modeling and database design
  • Working knowledge of frontend frameworks such as React or Vue
  • Experience packaging services with Docker
  • Hands-on experience with AWS services including EC2, IAM, VPC, and RDS, or comparable cloud platforms
  • Strong ownership of automated testing and continuous integration pipelines
  • Consistent application of secure software development practices
  • Familiarity with cybersecurity
  • Experience with Kubernetes, especially self-managed or on-premises clusters
  • Experience with vector databases such as Pinecone or Milvus, or with embedding-based retrieval and RAG systems
  • Experience using AI-agent evaluation, guardrail, or observability tools
  • Experience in air-gapped, highly regulated, or secure enterprise environments

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