About the role
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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