GenAI DevOps Engineer

GenAI DevOps Engineer at Elbit Systems Israel

Elbit Systems is seeking a skilled and motivated DevOps Engineer with a strong passion for GenAI to join their Enterprise GenAI Group in Haifa. This role is crucial for building, operating, and scaling the organization's GenAI platform.

Key Responsibilities

• Lead DevOps practices within the GenAI domain, collaborating with AI engineers, software engineers, infrastructure teams, and cybersecurity to transform GenAI capabilities from experimentation into scalable, production-grade enterprise services.
• 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 for 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 is an advantage.
• Experience supporting AI/ML/GenAI systems in production is an advantage.
• Experience with cloud platforms (Azure) and hybrid/on-prem environments is an advantage.
• Familiarity with monitoring, logging, and observability tools is an advantage.
• Experience working in regulated, security-sensitive enterprise environments is an advantage.
• Strong sense of ownership, problem-solving skills, and ability to work independently.

Key skills/competency

• GenAI
• DevOps
• CI/CD
• Kubernetes
• Docker
• Terraform
• Python
• Cloud Platforms
• AI/ML
• Production Deployment