GenAI Group DevOps Engineer
We are looking for A skilled and motivated DevOps Engineer with a strong passion for GenAI, to join Elbit's Enterprise GenAI Group at our Haifa site and play a key role in building, operating, and scaling the organization's GenAI platform You will lead DevOps practices within the GenAI domain, working closely with AI engineers, software engineers, infrastructure teams, and cybersecurity to transform GenAI capabilities from experimentation into scalable, production-grade enterprise services Come be the DevOps enabler of our AI transformation — responsible for the foundations that allow GenAI solutions to be reliably developed, deployed, monitored, and adopted across the company
In this role you will Design, build, and maintain CI/CD pipelines for GenAI services, agents, and platforms using tools such as GitLab CI and GitHub Actions Operate and scale containerized GenAI workloads across cloud environments (Azure and AWS) Ensure high availability, reliability, observability, and performance of AI services Manage infrastructure as code using tools such as Terraform or Pulumi to enable repeatable, version-controlled environment provisioning Collaborate with AI engineers to enable safe, repeatable, and governed deployment of GenAI platforms and solutions Support the full lifecycle of GenAI solutions from development and experimentation to production deployment Implement monitoring, logging, versioning, and rollback mechanisms for GenAI solutions, MCPs, agents, and pipelines Support deployment and operation of LLM serving infrastructure (e.g., vLLM, Ollama, TGI) including GPU workload scheduling and resource management Promote DevOps best practices, automation, documentation, and a culture of ownership Participate in cross-organizational initiatives supporting large-scale GenAI adoption Produce and maintain technical documentation including runbooks, architecture diagrams, and operational playbooks
Requirements
- At least 3 years of hands-on experience as a DevOps Engineer
- Strong experience with Linux environments and scripting (Python preferred)
- Hands-on experience with containerization and orchestration (Docker, Kubernetes)
- Experience designing and operating CI/CD pipelines for production systems
- Hands-on experience with Infrastructure as Code (Terraform, Pulumi, or equivalent)
- Experience with Vector Databases (ElasticSearch, Weaviate, pgvector) in a RAG or GenAI pipeline context - advantage
- Experience supporting AI/ML/GenAI systems in production - advantage
- Experience with cloud platforms (Azure) and hybrid/on-prem environments - advantage
- Familiarity with monitoring, logging, and observability tools - advantage
- Experience working in regulated, security-sensitive enterprise environments - advantage
- Strong sense of ownership, problem-solving skills, and ability to work independently
- Only relevant applications will be answered*
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