Staff DevOps Engineer

Cellebrite

. Design, develop, and maintain automation processes for deploying large-scale, enterprise-grade applications, including AI/ML workloads and pipelines .

Posted 11/2/2026full-timePetah Tikva • IsraelLeadWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in designing and maintaining AI/ML infrastructure on AWS, including Amazon Bedrock and Kubernetes, while ensuring high availability and reliability. Strong capability in leveraging AI tools for DevOps processes and guiding teams in best practices for AI-augmented workflows.

Highest-signal resume keywords

AWS Infrastructure DevelopmentAI/ML Systems Production ExperienceAmazon Bedrock ProficiencyKubernetes ContainerizationInfrastructure as Code (Terraform, CloudFormation)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AWSAI/ML SystemsAmazon BedrockSageMakerKubernetesTerraformCloudFormationDevOps Release ManagementAutomation ScriptingNetworking

Soft Skills

Excellent Communication SkillsTeam GuidanceContinuous Learning Mindset

Tools & Technologies

Google Cloud Platform (GCP)GitHub ActionsAI Coding AssistantsAgentic WorkflowsLLM-Powered Automation

Industry Keywords

AI InfrastructureHigh-Availability SystemsMulti-Cloud EnvironmentOperational MetricsDocumentation and Knowledge Base

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud PlatformKubernetesLinuxTerraform

About the role

Key responsibilities & impact

Design, develop, and maintain automation processes for deploying large-scale, enterprise-grade applications, including AI/ML workloads and pipelines
Serve as the go-to expert for CI/CD processes supporting Cellebrite’s cloud and AI products
Architect, deploy, and operate infrastructure for AI systems, including Amazon Bedrock, model endpoints, and inference pipelines
Use AI tools and agents in daily DevOps work to increase velocity, reduce toil, and improve quality
Stay current with AI models, frameworks, cloud AI services, and industry best practices, and apply relevant advances to team tooling and processes
Partner with R&D, Product Management, and Architecture to deliver operational metrics and feedback supporting high product availability
Investigate outages and other issues, including those affecting AI/ML services
Oversee documentation of issues and resolutions and maintain a knowledge base of known issues
Produce, oversee, and maintain architecture diagrams, system designs, and runbooks
Work with SREs, DevOps Engineers, and developers to solve problems and investigate anomalies
Participate in an on-call rotation to help maintain the 99.95% uptime SLO

Requirements

What you’ll need

7+ years of experience working with AWS, with a proven track record of building complex infrastructure
2+ years of hands-on experience working with AI/ML systems in production, applying best practices for reliability, cost, security, and scalability of AI infrastructure
Strong, hands-on experience with Amazon Bedrock and the broader AWS AI/ML stack, including SageMaker and vector databases
Demonstrated habit of using AI tools in daily engineering work, including AI coding assistants, agentic workflows, and LLM-powered automation
Continuous-learning mindset toward AI and curiosity about evolving AI capabilities
Working knowledge of Google Cloud Platform (GCP), with ability to operate and troubleshoot across a multi-cloud environment
Strong experience with networking, containerization using Kubernetes, and Linux system administration
Deep understanding of Infrastructure as Code, including Terraform and CloudFormation
Strong experience with Kubernetes, preferably AWS EKS
Experience scaling and maintaining high-availability production systems
Experience with DevOps release management, versioning, build management, automation scripting, and CI tools such as GitHub Actions
Excellent verbal and written communication skills in English
Ability to guide the team and provide best practices as a DevOps Tech Lead, particularly around AI infrastructure and AI-augmented workflows

Benefits

Comp & perks

99.95% uptime SLO participation through an on-call rotation